Correction. Central limit theorems for additive functionals of the simple exclusion process
Central Limit Theorem - Department of Mathematics and :中心极限定理的数学系
– Y is approximately
N[1006*0.36, (0.36)*(0.64)*1006] = N(362.16,231.8) (by central limit theorem)
Comments about normal approximation of the binomial : Rule of thumb is that it’s OK if np>5 and n(1-p)>5. “Continuity correction” Y is binomial. If we use the normal approximation to the probability that Y<k, we should calculate Pr(Y<k+.5) If we use the normal approximation to the probability that Y>k, we should calculate Pr(Y<k-.5)
3. Suppose the average amount produced is more than 11.0ml. Is that a rare event? Why or why not? If more than 11.0ml are made, what might that suggest?
Pr[ (Y-362.16)/15.2 < (352-362.16)/15.2] = Pr(Z < -0.67) = 0.25
Normal Approximation to the binomial CDF
常用色谱术语(中英文对照)
常用色谱术语(中英文对照)色谱图 chromatogram色谱峰chromatographicpeak峰底peak base峰高h,peak height峰宽W,peak width半高峰宽Wh/2,peak width athalf height 峰面积A,peak area拖尾峰tailing area前伸峰leading area假峰ghost peak畸峰distorted peak反峰negative peak拐点inflection point原点origin斑点spot区带zone复班multiple spot区带脱尾zone tailing基线base line基线漂移baseline drift基线噪声N,base line noise统计矩moment一阶原点矩γ1,first origin moment二阶中心矩μ2,second central moment三阶中心矩μ3,third central moment液相色谱法liquidchromatography,LC液液色谱法liquid liquidchromatography,LLC液固色谱法liquid solidchromatography,LSC正相液相色谱法normal phaseliquid chromatography反相液相色谱法reversed phaseliquid chromatography,RPLC 柱液相色谱法liquid columnchromatography高效液相色谱法high performanceliquid chromatography,HPLC尺寸排除色谱法size exclusionchromatography,SEC凝胶过滤色谱法gel filtrationchromatography凝胶渗透色谱法gel permeationchromatography,GPC亲和色谱法affinitychromatography离子交换色谱法ion exchangechromatography,IEC离子色谱法ionchromatography离子抑制色谱法ion suppressionchromatography离子对色谱法ion pairchromatography疏水作用色谱法hydrophobicinteraction chromatography制备液相色谱法preparativeliquid chromatography平面色谱法 planarchromatography纸色谱法 paperchromatography薄层色谱法 thin layerchromatography,TLC高效薄层色谱法 highperformance thin layerchromatography,HPTLC浸渍薄层色谱法 impregnatedthin layer chromatography凝胶薄层色谱法 gel thin layerchromatography离子交换薄层色谱法 ion exchangethin layer chromatography 制备薄层色谱法 preparativethin layer chromatography薄层棒色谱法 thin layer rodchromatography液相色谱仪 liquidchromatograph制备液相色谱仪preparativeliquid chromatograph 凝胶渗透色谱仪 gel permeationchromatograph涂布器 spreader点样器 sampleapplicator色谱柱 chromatographiccolumn棒状色谱柱 monolith columnmonolith column 微粒柱 microparticlecolumn填充毛细管柱 packedcapillary column空心柱 open tubularcolumn微径柱 microborecolumn混合柱 mixed column组合柱 coupled column预柱 precolumn保护柱 guard column预饱和柱 presaturationcolumn浓缩柱 concentratingcolumn抑制柱 suppressioncolumn薄层板 thin layerplate浓缩区薄层板 concentratingthin layer plate荧光薄层板 fluorescencethin layer plate反相薄层板reversed phasethin layer plate梯度薄层板 gradient thinlayer plate烧结板 sintered plate展开室 developmentchamber往复泵 reciprocatingpump注射泵 syringe pump气动泵 pneumatic pump蠕动泵 peristalticpump检测器 detector微分检测器 differentialdetector积分检测器 integraldetector总体性能检测器 bulk propertydetector溶质性能检测器 solute propertydetector(示差)折光率检测器 [differential] refractive indexdetector 荧光检测器 fluorescencedetector紫外可见光检测器 ultravioletvisible detector电化学检测器 electrochemicaldetector蒸发(激光)光散射检测器 [laser] light scattering detector光密度计 densitometer薄层扫描仪 thin layer scanner柱后反应器 post-columnreactor体积标记器 volume marker记录器 recorder积分仪 integrator馏分收集器 fractioncollector工作站 work station固定相 stationaryphase固定液 stationaryliquid载体 support柱填充剂 column packing化学键合相填充剂 chemicallybonded phase packing薄壳型填充剂 pellicularpacking多孔型填充剂 porous packing吸附剂 adsorbent离子交换剂 ion exchanger基体 matrix载板 support plate粘合剂 binder流动相 mobile phase洗脱(淋洗)剂 eluant,eluent展开剂 developer等水容剂 isohydricsolvent改性剂 modifier显色剂 color[developing] agent死时间 t0,dead time保留时间 tR,retentiontime调整保留时间 t''R,adjustedretention time死体积 V0,dead volume保留体积 vR,retentionvolume调整保留体积 v''R,adjustedretention volume柱外体积 Vext,extra-columnvolune粒间体积 V0,interstitialvolume(多孔填充剂的)孔体积 VP,pore volume of porous packing 液相总体积 Vtol,total liquidvolume洗脱体积 ve,elutionvolume流体力学体积 vh,hydrodynamicvolume相对保留值 ri.s,relativeretention value分离因子α,separation factor流动相迁移距离 dm,mobile phase migration distance流动相前沿 mobile phasefront溶质迁移距离 ds,solute migration distance比移值 Rf,Rf value高比移值 hRf,high Rf value相对比移值 Ri.s,relative Rfvalue保留常数值 Rm,Rm value板效能 plateefficiency折合板高 hr,reduced plate height分离度 R,resolution液相载荷量 liquid phaseloading离子交换容量 ion exchangecapacity负载容量 loadingcapacity渗透极限 permeabilitylimit排除极限 Vh,max,exclusion limit拖尾因子 T,tailing factor柱外效应 extra-columneffect管壁效应 wall effect间隔臂效应 spacer armeffect边缘效应 edge effect斑点定位法 localization ofspot放射自显影法 autoradiography原位定量 in situquantitation生物自显影法 bioautography归一法 normalizationmethod内标法 internalstandard method外标法 external standardmethod叠加法 addition method普适校准(曲线、函数)calibration function or curve[function] 谱带扩展(加宽) band broadening(分离作用的)校准函数或校准曲线 universalCalibration function or curve [of separation]加宽校正 broadeningcorrection加宽校正因子 broadeningcorrection factor溶剂强度参数ε0,solvent strength parameter洗脱序列 eluotropicseries洗脱(淋洗) elution等度洗脱 gradientelution梯度洗脱 gradientelution(再)循环洗脱 recycling elution线性溶剂强度洗脱 linear solventstrength gradient 程序溶剂 programmedsolvent程序压力 programmedpressure程序流速 programmed flow展开 development上行展开 ascendingdevelopment下行展开 descendingdevelopment双向展开 two dimensionaldevelopment环形展开 circulardevelopment离心展开 centrifugaldevelopment向心展开 centripetaldevelopment径向展开 radialdevelopment多次展开 multipledevelopment分步展开 stepwisedevelopment连续展开 continuousdevelopment梯度展开 gradientdevelopment匀浆填充 slurry packing停流进样 stop-flowinjection阀进样 valve injection柱上富集 on-columnenrichment流出液 eluate柱上检测 on-columndetection 柱寿命 column life柱流失 column bleeding显谱 visualization活化 activation反冲 back flushing脱气 degassing沟流 channeling过载 overloading(文章来源:网络)。
仪器分析常见术语英汉对照
仪器分析常见术语英汉对照Chapter 1 Preface/绪论analytical chemistry/chemical analysis/ instrumental analysis/分析化学/化学分析/仪器分析spectral analysis/光谱分析 electroanalytical chemistry/电分析化学chromatography/色谱法 methods for inorganic species/ 无机物的分析 methods for organic and biochemical species/有机物、生物化学物质的分析description of validation parameters/有效参数的描述precision/精密度 accuracy/准确度 sensitivity/灵敏度 detection limit/检出限quantitation limit/定量限 linearity/线性 linear range/线性范围absolute error/绝对误差 relative error/相对误差 systematic error/系统误差determinate error/可定误差 accidental error/随机误差 indeterminate error/不可定误差debiation/偏差 average debiation/平均偏差 relative average debiation/相对平均偏差 standerd deviation;S/标准偏差(标准差) relatibe standard deviation;RSD/相对平均偏差coefficient of variation/变异系数 propagation of error/误差传递 significant figure/有效数字 partial least squares method ,PLS/偏最小二乘法Chapter 2 Introduction to Optical Methods of Analysis/光学分析导论properties of electromagnetic radiation/电磁辐射的性质 wave properties/波性质 the particle Nature of light: photons/光的粒子性质 interaction of radiation and matter/辐射与物质的相互作用 the electromagnetic spectrum/电磁波谱spectroscopic measurements/光谱测量 radiation absorption/辐射吸收 absorption process/吸收过程 absorption spectra/吸收光谱 limits to Beer's Law/比尔定律的局限性 qualitative sqectrometric analysis/光谱定性分析semiquantitative spectrometric analysis/光谱半定量分析 quantitative spectrometric analysis/光谱定量分析 instruments for optical spectrometry/光谱仪器 spectrophotometer /光谱仪instrument components/仪器的组成部件 optical materials/光学材料 spectroscopic sources/光源 wavelength selectors/单色器 sample containers/样品池spectrophotometer/分光光度计 single beam spectrophotometer/单光束分光光度计double beam spectrophotometer/双光束分子光光度计 dual wavelength spectrophotometer/双波长分光光度计 colorimeter/比色计 visual colorimeter/目视比色计 photoelectric coolorimeter/光电子比色计 holographic grating/全息光栅interference filter/干涉滤光片 calibration filter/校准滤光片 neutral filter/中性滤光片 absorption cell/cuvette/吸收池/比色皿 photocell/photovoltaic cell/光电池photomultiplier/光电倍增管 detecting and measuring radiant energy/辐射能检测signal processors and readouts/信号处理和数据输出molecular Luminescence Analysis/分子发光分析 molecular fluorescence spectroscopy/分子荧光分光光度法 theory of molecular fluorescence/分子荧光光谱法理论 effect of concentration on fluorescence intensity/影响荧光强度的因素 molecular phosphorescence/分子磷光 chemiluminescence methods/化学发光法Chapter 3 Atomic Emission Spectrometry(AES)/原子发射光谱origins of atomic spectra/原子光谱的起源 formation of atomic emission spectra/原子发射光谱的产生 outer electron/外层电子 electron transition/电子跃迁production of atoms and ions/原子和离子的产生 excited potential/激发电位ionization potential/电离电位 transition rule/跃迁定则 energy level diagram/能级图 characteristic spectrum/特征光谱 spectrum line intensity /谱线强度self-absorption and self reversal of spectrum line /谱线的自吸与自蚀 atomization efficiency/原子化效率 atomic line/原子线 resonance line/共振线 sensitive line/灵敏度 Boltzmann distribution/波尔兹曼分布定律 Boltzmann factor/波尔兹曼因子Boltzmann constant/波尔兹曼常数 device and instrument of AES /原子发射光谱分析装置与仪器 types and process of AES /仪器类型与流程 slit/ 狭缝 diffraction grating/衍射光栅 steeloscope/看谱镜 photoelectric direct reading spectrometer/光电直读光谱计 flame photometer/火焰光度计 excitation light source/激发光源 spectrum projictor/映谱仪 spectral photographic plate/光谱感光板microphotometer,microdens-tometer/测微光度计 spectrograph/摄谱仪 plsma source/等离子体[光]源 glow discharge/辉光放电 high firequency discharge/高频放电inductively coupled high frequency plasma torch/电感耦合高频等离子体焰炬capacitively coupled high frequency plasma torch/电容耦合高频等离子体焰炬capacitively coupled microwave plasma torch/电容耦合微波等离子体焰炬 laser microprobe/激光微探针 plate/相板(又称干板) flame spectrometer /火焰光度计 arc and electric spark emission spectrometer/电弧和电火花发射光谱仪 sample introduction systems/样品引入系统 multi-element/多元素 plasma sources/等离子体光源 electrothermal atomizers/电热原子化器 other atomizers/其它原子化器 sources of nonlinearity in atomic emission spectrometry/非线性光源plasma emission spectrometry/等离子发射光谱 direct current plasma jet(DCP)/直流等离子体喷焰 inductively coupled plasma(ICP)/电感耦合等离子体 principle and feature of ICP-AES /电感耦合等离子体发射光谱原理和特点 microwave induced plasma( MIP)/微波感生等离子体 interferences in plasma and flame atomic emission spectroscopy/等离子体和火焰原子光谱中的干扰 matrix interference/基体干扰photomultiplier tube (PMT)/光电倍增管 charge injection detector(CID)/电荷注入式检测器 qualitative and quantitative analysis method /定性和定量分析方法linear dispersion/曲线 angular dispersion/线色散 angular dispersion/角色散reciprocal linear dospersion/倒数线色散 resolving power,resolution/分辨本领spectral line interfernce/谱线干扰 spectral interference/光谱干扰 ionization interference/电离干扰 chemical interference/化学干扰 emission interference/发射干扰 matrix modifier/基体改进剂 spectral buffer/光谱缓冲剂 background absorption/背景吸收 maximum absorption/最大吸收 molecular absorption/分子吸收background absorption Correction/背景吸收校正 enhancement effect/增感效应depression effect/抑制效应Chapter 4 Atomic Absorption Spectrometry and Atomic Fluorescence Spectrometry /原子吸收光谱和原子荧光光谱absorption line/吸收线 resonance line/共振线 line profile/分析线 line profile/谱线轮廓 line width/谱线宽度 entegrated absorption method/积分吸收法 peak absorption method/峰分吸收法 Zeeman effect/塞曼效应 atomization/原子化 line width effects in atomic absorption/原子吸收中的变宽效应 flame atomic absorption/火焰原子吸收 relaxation processes/弛豫过程 atomic absorption with electrothermal atomization/ 原子吸收与电热原子化 interferences in atomic absorption/原子吸收中的干扰 fame atomizers/火焰原子化器 atomic fluorescence spectrometry/原子荧光光谱法 fluorescent species/荧光物质类型 fluorescence instruments/荧光光谱仪applications of fluorescence methods/荧光法的应用Chapter 5 Ultraviolet and Visible Absorption Spectroscopy/紫外-可见吸收光谱ultraviolet-visible absorption spectrometry/紫外可见吸收光谱 ultraviolet-visible photometers and spectrophotometers/紫外—可见分光光度计 spectrophotometric methods/分光光度法 apsorbing species/吸收类型 single-beam Instruments/单光束分光光度计 double-beam instruments/双光束分光光度计 multichannel instruments/多通道仪器 shoulder peak/肩峰 end absorbtion/末端吸收 chromophore/吸收生色团auxochrome/助色团 electron donating group/供电子取代基 electron with-drawing group/吸电子取代基 red shift/红移 blue shift/蓝(紫)移 bathochromic shift/长移hypsochromic shift/短移 hyperchromic effect/增色效应(浓色效应) hypochromic effect/减色效应(淡色效应) strong band/强带 weak band/弱带 absorption band吸收带 transmitance,T/透光率 absorbance/吸光度 band width/谱带宽度 stray light/杂散光 noise/ 噪声 dark noise/暗噪声 signal shot noise/散粒噪声 blazed grating/闪耀光栅 holographic graaing/全息光栅 photodiode array detector/光二极管阵列检测器convolution spectrometry/褶合光谱法 convolution transform,CT/褶合变换 wavelet transform,WT/离散小波变换 multiscale analysis/多尺度细化分析Chapter 6 Infrared Absorption Spectroscopy/红外吸收光谱infrared ray,IR/红外线 mid-infrared absorption spectrum/Mid-IR/中红外吸收光谱far infrared /Far-IR/远红外 near infrared/近红外 microwave spectrum,MV/微波谱infrared spectroscopy/红外吸收光谱法 infrared spectrophotometry/红外分光光度法mode of vibration/振动形式 stretching vibration/伸缩振动 symmetrical stretchingvibration/对称伸缩振动 asymmetrical stretching vibration/不对称伸缩振动 bending vibration/弯曲振动 formation vibration/变形振动 in-plane bending vibration,β/面内弯曲振动 scissoring vibration,δ/剪式振动 rocking vibration,ρ/面内摇摆振动out-of-plane bending vibration,γ/面外弯曲振动 wagging vibration,ω/面外摇摆振动twisting vibration ,τ/蜷曲振动 symmetrical deformation vibration ,δs/对称变形振动 asymmetrical deformation vibration, δas/不对称变形振动 ring prckering vibration/环折叠振动 charateristic avsorption band/特征吸收峰 characteristic frequency/特征频率 correlation absorption band/相关吸收峰 hybridization affect/杂化影响 ring size effect/环大小效应 intensity of absorption band/吸收峰的强度deactivation/去活化过程 vibrational relaxation(VR)/振动弛豫 vibration spectrum/振动光谱 internal Conversion(IC)/内转换 external conversion(EC)/外转换intersystem conversion(ISC)/系间跨跃 dichroism/二色性 wave number calibration/波数校准 group frequency/基团频率 cell-in -cell-ort method/池入-池出法 baseline/基线法 stray light/杂散法 infrared spectrophotometers/红外分光光度计 infrared absorption spectra/红外吸收光谱 absorption intensity/吸收强度 fundamental frequency band/基频谱带 spurious band/乱真谱带 vibrational-rotational spectrum/振转光谱 instruments for infrared spectroscopy/红外光谱仪器fourier transform infrared spect-rometer(FTIR)/傅里叶这换红外光谱计 infrared source/红外光源 infrared beam condenser/红外光束聚光器 infrated polarizer/红外偏振器 studies of complex ions/络合物研究 dispersive infrared instruments/色散型红外光谱仪 fourier transform instruments/傅立叶变换红外光谱仪Chapter 7 Nuclear Magnetic Resonance (NMR) Spectroscopy/核磁共振波谱学introduction to NMR Spectroscopy/核磁谱的简介 definition of NMR Spectroscopy/核磁谱学的定义 NMR History/核磁的历史 properties of nuclei/核的性质 nuclear magnetic resonance,NMR/核磁共振 NMR spectrum/核磁共振波谱 NMR spectroscopy/核磁共振波谱法 continuous wave NMR,CW NMR/连续波核磁共振 fourier transformation NMR spectrum/ FT-NMR/傅立叶变换核磁共振谱 proton magnetic resonance spectrum,PMR/质子核磁共振谱 1H NMR and 13C NMR spectrum/氢谱和碳-13核磁共振谱 spin angular momentum/自旋角动量 magnetogyric ratio/磁旋比 magnetic quantum number,m/磁量子数precession/进动 relaxation mechanism/弛豫历程 local diamagnetic shielding/局部抗磁屏蔽 shielding constant/屏蔽常数 swept field/扫场 seept frequency/扫频schematic NMRspectrometer/核磁仪的概图 magnetic anisotropy/磁各向异性 long range shielding effect/远程屏蔽效应 magnetic eqivalence/磁等价 spin system/自旋系统chemical shift/化学位移 standard for chemical shift/核磁的内标物 shielding and deshielding/屏蔽和去屏蔽效应 spin-spin coupling/自旋-自旋耦合 J-coupling/ J-耦合spin-spin coupling/自旋-自旋偶合 spin=spin splitting/自旋-自旋分裂 coupling constant/耦合常数 decoupling/去耦 nodal plane/结面 factors to affect 1Hchemical shift/影响氢化学位移的因素 signalsplitting for 1H/氢谱的裂分 chemical shift - 13C-NMR/碳谱的化学位移 13C-NMR integration/碳谱中积分 interpreting NMR spectra/核磁谱的解析 2D NMR/二维核磁共振 singlet,s/单峰 doublet,d/双峰 triplet,t/三重峰quartet/ quintet/ sextet/四重峰/五重峰/六重峰 geminal coupling /vicinal coupling/偕偶/邻偶 long range coupling/远程偶合 first order spectrum/一级光谱 second order spectrum/二级光谱(二级图谱) C-H correlated spectroscopy,C-H COSY/C-H光谱Chapter 8 Introduction to Electrochemistry/电化学导论electrochemical analysis/电化学分析 electrolytic analysis method/电解法electtogravimetry/电重量法 coulometry/库仑分析法(电量分析) coulometric titration/库仑滴定法 conductometry/电导法 conductometric analysis/电导分析法conductometric titration/电导滴定法 potentiometry/电位分析法 dirext potentiometry直接电位法 potentiometric titration/电位滴定法 voltammetry/伏安法polarography/极谱法 stripping method/溶出法 amperometric titration/电流滴定法chemical double layer/化学双电层 phase boundary potential/相界电位 electrode potential/金属电极电位 chemical cell/化学电池 liquid junction boundary/液接界面galvanic cell/原电池 electrolytic cell/电解池 cathrode/负极 anode/正极eletromotive force/电池电动势 potentials/电极电势 Plank constant/普朗克常数Nernst equation/能斯特方程 indicator electrode/指示电极 reference electroade/参比电极Chapter 9 Potentiometry/电位法principles of potentiometric measurements/电位法测定原理 direct potentiometry/直接电位法 potentiometric titrations/电位滴定法 standard hydrogen electrode/标准氢电极 primary reference electrode/一级参比电极 standard calomel electrode/饱和甘汞电极 silver silver-chloride electrode/银-氯化银电极 liquid junction boundary/液接界面 asymmetry potential/不对称电位 apparent PH /表观PH值combination PH electrode/复合PH电极 ion selective electrode/离子选择电极 sensor/敏感器 crystalline electrodes/晶体电极 homogeneous membrance electrodes/均相膜电极 heterog eneous membrance electrodes/非均相膜电极 non- crystalline electrodes/非晶体电极 rigid matrix electrode/刚性基质电极 electrode with a mobile carrier/流流体载动电极 gas sensing electrodes/气敏电极 enzyme electrodes/酶电极 glass electrodes/玻璃电极 liquid membrane electrodes/液膜电极 solid-state electrodes/固体电极 selectivity coefficient/选择性系数 electrode-ealibration method/电极校正方法 standard-addition method/标准加入法Chapter 10 Electrolytical Analysis and Coulometry/电解分析法和库仑法bulk electrolysis: electrogravimetry and coulometry/整体电解:电重量法和库仑法controlled-Current electrolytical analysis/控制电流电解法 controlled -Potentil electrolytical analysis/控制电势电解法 choice of negative potential/负极电位的选择 controlled-Potential coulometry/控制电势库仑法 coulometric titration/库仑滴定法 coulometric methods/库仑分析法Chapter 11 Voltammetry and Polarograph/伏安法和极谱法polarography/极谱法 polarogram/极谱图 polarography Equation/极谱波方程linear-sweep Voltammetry /线性扫描伏安法 cyclic voltammetry/循环伏安法 pulse polarographic and voltammetri cmethods/脉冲极谱和伏安法 polarography catalytical waves/极谱催化波 parallel polarographic catalytic wave/极谱平行催化波 hydrogen catalytic wave/氢催化波 adsorptive complex wave/络合物吸附波 stripping voltammetriy/溶出伏安法 anodic stripping voltammetry/阳极溶出伏安法 cathodic stripping voltammetry/阴极溶出伏安法Chapter 12 Chromatography: Theory and Concepts/色谱分析法理论与概念concepts and terms/概念及术语 chromatography/色谱法(层析法) chromatography processor/色谱过程 stationary phase/固定相 mobile phase/流动相 peak height/峰高peak width,W/峰宽 peak width at half height,W1/2 or Y1/2/半峰宽leading peak/前延峰 tailing peak/拖尾峰 symmetry factor,fs/对称因子 retention time/保留时间 retention volume/保留体积 dead time/死时间 asjusted retention time/调整保留时间 isotherm line/等温线 height equivalent to atheoretical plate/理论塔板高度分离度resolution normalization method/归一化法 external standardization外标法 distribution cofficient/分配系数 partition coefficient/狭义分配系数 plate theory/塔板理论 number of theoretical plates/理论塔板数 rate theory/theory of rate/速率理论 resolution ,R/分离度 separation number,SN/分离数 relative Rf, Rr/相对比移值 gas chromatography,GC/气相色谱法 liquid cromatography,LC/液相色谱法planar, plane chromatography//平板色谱法 paper chromatography/纸色谱法 thin layer chromatography ,TLC/薄层色谱法thin film chromatography/薄膜色谱法 capillary electrophoresis,CE/毛细管电泳法high-performance/高效 high performance capillary electroporesis,HPEC/高效毛细管电泳法 high performance liquid chromatography,HPLC/高效液相色谱法 normal-phase/正相 recersed-phase/反相 ion-exchange/离子交换 gel-filtration/凝胶过滤chromatography applications database/色谱应用数据库Chapter 13 Gas chromatography/气相色谱法chemically bonded phase/化学键合相 polydiethylene glycol succinate,PDEGS,DEGS/丁二酸二乙二醇聚酯 GDX/高分子多孔微球 STY/苯乙烯; EST/乙基乙烯苯; DVB/二乙烯苯wall coated open tubular column,WCOT/涂壁毛细管柱 supprot coated open tubular column,SCOT/载体涂层毛细管柱 thermal conductivity detector,TCD/热导检测器hydrogen flame ionization detector,FID/氢焰离子化检测器 electron capture detector ,ECD/电子捕获检测器 noise,N/噪声 drift,d/漂移 column chromatography/柱色谱法 column selector/柱子的选择 packed column/填充柱 capillary column/毛细管柱microbore packed column 微填充柱 instruments in gas chromatography/气相色谱仪GC/MS: instruments and applications/气相色谱-质谱联用技术Chapter 14 High performance liquid chromatography/高效液相色谱liquid –solid chromatography adsorption ,LSC/液-固吸附色谱(液固色谱法)liquid-liquid partition chromatography液-液分配色谱法(分配色谱) normal phase,NP/正相 reversed phase, RP/反相 octadecylselyl,ODS/十八烷基 isocraic elution/恒组成溶剂洗脱 gradient elution/梯度洗脱 ion exchange chromatography,IEC/离子交换色谱法 chemically bonde phase/化学键合相 bonded phase chromatography,BPC/键合相色谱法 chemically bonded-phase chromatography/化学键合相色谱法 ion chromatography,IC/离子色谱法 paired ion chromatography,PIC/离子对色谱法 ion suppression chromatography,ISC/离子抑制色谱法 steric exclusion chromatography,SEC/空间排阻色谱法 size-exclusion chromatography/尺寸排阻色谱gel chromatography/凝胶色谱法 gel permeation chromatography,GPC/凝胶渗透色谱法gel filtration chromatography,GFC/凝胶过滤色谱法 permeation coefficien;Kp/渗透系数 chiral chromatography,CC/手性色谱法 chiral stationary phase,CSP/手性固定相cyclodextrin chromatography,CDC/环糊精色谱法 micellar chromatography,MC/胶束色谱法 affinity chromatography,AC/亲和色谱法 supercritical fluid chromatography,SFC/超临界流体色谱法 end capping/封尾、封顶、遮盖 capillary electrophoresis/毛细管电泳 instruments in capillary electrophoresis/毛细管电泳仪 electroosmotic flow/电渗流 criticak micolle concentration ,CMC/临界胶束浓度 DNA sequencing and capillary array electrophoresis/DNA序列分析及毛细管阵列电泳ultraviolet detector,UVD/紫外检测器 fluorophotomeric detector,FD/荧光检测器 ECD/电化学检测器 RID/示差折光检测器 photodiode array detector ,DAD/光电二极管检测器3D-spectrochromatogram/三维光谱-色谱图 evaporative light scatteringdetector,ELSD/蒸发光散射检测器 ampere detector,AD、安培检测器 high performance capillary electrophoresis,HPCE、高效毛细管电泳法 mobility/淌度 electrophoresis/电泳 electroosmosis/电渗 hydrodynamic injection/动力进样 electrokinetic injection/电动进样 capillary zone electrophoresis,CZE/毛细管区带电泳法 micellar electrokinetic capillary chromatography,MECC/胶束电动毛细管色谱 capillary gel electrophoresis,CGE/毛细管凝胶电泳 sieving筛分 thin layer plate/薄层板;TLC/薄层色谱法 adsorption/吸附 activation/活化 deactivation/脱活性 degree of cross linking/交联度 exchange capacity/交换容量 developing solvent ,developer/展开剂Chapter 15 Mass Spectrometry /质谱分析法mass spectrum,MS/质谱 bar graph/棒图 selected ion monitoring ,SIM/选择离子检测direct probe inlet ,DPI/直接进样 interface/接口 gas chromatography-mass spectrometry,GC-MS/气相色谱-质谱联用 high performance liquidchromatography-mass spectrometry,HPLC-MS /高效液相色谱-质谱联用ionizationmethods/离子化方法 electron impact source,EI/电子轰击离子源 fast atom bombardment ,FAB/快速原子轰击离子源 chemical ionization source,CI/化学离子源field ionization,FI/场电离 field desorptiion,FD/场解析 matrix assisted laser desorption (MALDI)/基质辅助的激光解吸 electro spray ionization ( ESI )/电喷雾 mass analyzer/质量分析器 magnetic-sector mass spectrometer/磁质谱仪 quadrupole mass spectrometer/四极杆质谱仪(四极质谱仪)amu/原子质量单位 ion abundance/离子丰度 relative avundance/相对丰度(相对强度) base peak/基峰 mass range/质量范围 resolution/分辨率 sensitivity/灵敏度 S/N /信噪比 molecular ion/分子离子 fragment ion/碎片离子 isotopic ion/同位素离子metastable ion/亚稳离子 metastable peak/亚稳峰 parent ion/母离子 daughter ion/子离子 odd electron/含奇数个电子的离子 even eletron,EE/含偶数个电子的离子homolytic cleavage/均裂 heterolytic cleavage/异裂(非均裂) hemi-homolysis cleavage/半均裂 rearragement/重排 MW/分子量α-cleavage/α-裂解 relative Abundance of Isotopes/同位素的相对丰度 isotopic Ratio from the Spectra/质谱中的同位素比例 magnetic sector analyzer/磁分析器 time of flight analyzer/飞行时间分析器 quadrupole analyzers/四极质量分析器 fourier transform ioncyclotron/傅立叶离子回旋共振分析器 MS interpretation and fragmentation/质谱解析和化合物裂解presentation of data/数据表达 determination of Molecular Mass/分子量的测量 high resolution mass spectrometry/高分辨质谱 important fragmentation patterns in EI/ 电子轰击电离下的重要裂解方式patterns of different organic compounds’ fragmentation/不同类型有机物的裂解模式 hyphenated MS techniques/质谱联用技术。
均匀经验过程几乎处处中心极限定理的一个注记
均匀经验过程几乎处处中心极限定理的一个注记张勇【摘要】设{ξ1,ξ2,…,ξn}为来自[0,1]上服从均匀分布的独立同分布样本,产生的经验过程为Fn(t)=n-1/2∑(I{ξi≤t} -t),0≤t≤1;‖·‖表示一致模,即‖Fn‖=sup0≤t≤1|Fn(t)|;U为D[0,1]上的Brown桥,‖U‖=sup|0≤t≤1 |U(t)|.利用概率强收敛工具,得到了关于‖Fn‖及sup 0≤t≤1 Fn(t)的形如lim n→∞ 1/lognn∑k=1 1/k I{Fk‖≤x}=P{‖U ‖≤x}=1+2∞∑k=1(-1)ke-2k2x2a.s.的几乎处处中心极限定理.【期刊名称】《吉林大学学报(理学版)》【年(卷),期】2011(049)004【总页数】3页(P687-689)【关键词】均匀经验过程;几乎处处中心极限定理;Brown桥【作者】张勇【作者单位】吉林大学数学学院,长春130012【正文语种】中文【中图分类】O211.4几乎处处中心极限定理(ASCLT)最早分别由Brosamler[1]和Schatte[2]独立提出并研究的. 而对于i.i.d.随机变量列有下述几乎处处中心极限定理: 设{Xn,n≥1}是独立同分布随机变量序列, 则∀x, 有本文I{·}表示示性函数, Φ(·)表示标准正态分布的分布函数. ASCLT问题在随机模拟方面应用广泛[3]. 目前, ASCLT问题已取得许多研究结果: Lacey等[4]针对i.i.d.随机变量列, 在二阶矩的条件下, 证明了ASCLT成立; Peligrad等[5]针对平稳α-混合随机变量列、平稳ρ-混合随机变量列以及平稳PA随机变量列, 在的条件下, 证明了ASCLT成立; 董志山等[6]针对平稳NA和LNQD随机变量列, 在的条件下, 证明了ASCLT和FASCLT成立; 文献[7-10]在不同的条件下分别得到了几乎处处中心极限定理.本文恒假设{ξ1,ξ2,…,ξn}为来自[0,1]上服从均匀分布的独立同分布样本, 产生的经验过程为表示一致模, 即为D[0,1]上的Brown桥,Dehling等[11]对相依数据下的经验过程给出了一种新的处理方法; Drees等[12]得到了由族函数生成经验过程的极限定理; 王芳[13]得到了关于Fn(t)的几乎处处中心极限定理. 本文将文献[13]的结果推广到由随机样本{ξ1,ξ2,…,ξn}产生的经验过程, 即关于‖Fn‖和的几乎处处中心极限定理.引理1 由[0,1]上服从均匀分布、独立同分布的样本{ξ1,ξ2,…,ξn}产生的经验过程Fn(t)弱收敛于D[0,1]上的Brown桥U, 即Fn(t)⟹U.证明: 参见文献[14]中的定理2.引理2 设{ξ1,ξ2,…,ξn}为来自分布函数F的独立同分布样本, 记则存在正常数C, 使得对所有的n及所有的F和正数r, 有P{Dn≥r/n1/2}≤Ce-Cr2.证明: 参见文献[15]中的定理1.引理3 设{ξn,n≥1}为一零均值一致有界的随机变量序列, 再假设|Eξkξl|≤C(k/l)ε对于任意的1≤k<l≤n和某个ε>0成立, 则有证明: 参见文献[7]中的引理2.下面给出本文的主要结果.定理1 对于∀x>0, 有(1)证明: 由引理1知, {Fn(t),n≥1}弱收敛于D[0,1]上的Brown桥U, 于是由连续映射定理[16]知(2)设f(x)是一有界的Lipschitz函数, 并且其Radon-Nikodyn导数为f′(x), 满足|f′(x)|≤Γ. 则由式(2)知Ef(‖Fn‖)→Ef(‖U‖), n→∞.(3)另一方面, 由文献[5]中第二节及文献[16]中定理7.1知, 式(1)等价于(4)因此要证明式(1), 只需证明下式即可:(5)令则对于任意的1≤k<l≤n, 有Cov(Zk,Zl)=Cov(Zk,Zk,l)+Cov(Zk,Zl-Zk,l)=∶I1+I2.(6)由样本的独立性知,I1=0.利用f的Lipschitz性和有界性及引理2, 有从而由式(6)~(8)及引理3知式(5)成立, 即定理1的第一个等号成立. 而定理1的第二个等号可由文献[16]中的式(11.39)直接得到.定理2 对于∀x>0, 有(9)定理2的证明过程与定理1类似.参考文献【相关文献】[1] Brosamler G A. An Almost Everywhere Central Limit Theorem [J]. Math Proc Cambridge Philos Soc, 1988, 104(3): 561-574.[2] Schatte P. On Strong Versions of the Central Limit Theorem [J]. Math Nachr, 1988, 137: 249-256.[3] Fisher A. Convex-Invariant Means and a Pathwise Central Limit Theorem [J]. Adv Math, 1987, 63: 213-246.[4] Lacey M T, Phillip W. A Note on the Almost Sure Central Limit Theorem [J]. Statist Probab Lett, 1990, 9: 201-205.[5] Peligrad M, Shao Q M. A Note on the Almost Sure Central Limit Theorem [J]. Statist Probab Lett, 1995, 22: 131-136.[6] DONG Zhi-shan, YANG Xiao-yun. An Almost Sure Central Limit Theorem for NA and LNQD Random Variables [J]. Acta Mathematica Sinica, 2004, 47(3): 593-600. (董志山, 杨小云. NA及LNQD随机变量列的几乎处处中心极限定理 [J]. 数学学报, 2004, 47(3): 593-600.) [7] Gonchigdanzan K, Rempala G. A Note on the Almost Sure Limit Theorem for the Product of Partial Sums [J]. Appl Math Lett, 2006, 19(2): 191-196.[8] LI Yun-xia, WANG Jian-feng. An Almost Sure Limit Theorem for Products of Sumsunder Association [J]. Statist Probab Lett, 2008, 78(4): 367-375.[9] ZHANG Yong, YANG Xiao-yun, DONG Zhi-shan. An Almost Sure Central Limit Theorem for Products of Sums of Partial Sums under Association [J]. J Math Anal Appl, 2009, 355(2): 708-716.[10] Bercu B, Cénac P, Fayolle G. On the Almost Sure Central Limit Theorem for Vector Martingales: Convergence of Moments and Statistical Applications [J]. J Appl Probab, 2009, 46(1): 151-169.[11] Dehling H, Durieu O, Volny D. New Techniques for Empirical Processes of Dependent Data [J]. Stochastic Process Appl, 2009, 119(10): 3699-3718.[12] Drees H, Rootzén H. Limit Theorems for Empirical Processes of Cluster Functionals [J]. Ann Statist, 2010, 38(4): 2145-2186.[13] WANG Fang. Almost Sure Central Limit Theorem for Uniform Empirical Processes [J]. Journal of Capital Normal University: Natural Science Edition, 2006, 26(2): 9-11. (王芳. 均匀经验过程的几乎处处中心极限定理 [J]. 首都师范大学学报: 自然科学版, 2006, 26(2): 9-11.)[14] Pollard D. Convergence of Stochastic Process [M]. Berlin: Springer-Verlag, 1984.[15] Kiefer J, Wolfowitz J. On the Deviations of the Empiric Distribution Function of Vector Chance Variables [J]. Trans Amer Math Soc, 1958, 87: 173-186.[16] Billingsley P. Convergence of Probability Measures [M]. New York: Wiley, 1968.。
asymptomatic数学
asymptomatic数学题目:Asymptomatic: Exploring the Mysteries of a Mathematical ConceptIntroduction (150-200 words):Asymptomatic, a mathematical term that finds its origins in the Greek language, is a concept often encountered in various fields of study such as calculus, statistics, and engineering. Derived from the Greek words "a" meaning without, and "symptoma" meaning symptom, asymptomatic refers to a phenomenon where a function or a sequence approaches a particular value, becoming infinitely close to it, without ever quite reaching it. This intriguing concept has fascinated mathematicians for centuries and holds great significance in understanding the behavior and properties of mathematical functions. In this article, we will delve into the depths of asymptomatic, discussing its applications, importance, and various types in mathematics.Main Body (1000-1200 words):I. Understanding Asymptotes (300-400 words):Asymptotic behavior is often visualized through the concept of an asymptote, which serves as an imaginary line that a function gets arbitrarily close to but never intersects. Understanding asymptotes is crucial in comprehending the behavior of functions, particularly as the input values approach infinity or some other critical point. There are three main types of asymptotes worth exploring:1. Horizontal Asymptotes:When a function approaches a constant value as x tends to positive or negative infinity, we refer to it as having a horizontal asymptote. Horizontal asymptotes can be classified into three cases: when the function approaches a finite constant, infinity, or negative infinity as x approaches infinity or negative infinity.2. Vertical Asymptotes:Vertical asymptotes occur when a function approaches infinity or negative infinity as x approaches a constant value, often due todivision by zero or other singularities. These asymptotes indicate regions in which the function remains undefined or diverges.3. Oblique Asymptotes:Less commonly encountered, oblique asymptotes occur when a function approaches a slanted straight line as x tends to infinity or negative infinity. Oblique asymptotes can be identified through polynomial long division or by finding the limiting behavior of a function.II. Applications in Calculus (400-500 words):Asymptomatic plays a crucial role in calculus, particularly in studying limits, derivatives, and integrals. Here are a few key applications:1. Limits:Determining the limit of a function as x approaches a particular value allows us to understand its behavior in the vicinity of that point. Asymptotes play a vital role in defining the behavior offunctions as x approaches infinity or negative infinity. By analyzing the asymptotic behavior, mathematicians can determine the behavior of functions at various points and understand their convergence or divergence.2. Derivatives:Asymptotes can impact the derivative of a function at various points. For example, a function with a vertical asymptote may result in a derivative with singular points. Studying the behavior of a function near these points can provide insights into its overall behavior and shape.3. Integrals:Integrating functions with vertical asymptotes may lead to infinite results. Identifying these asymptotes helps mathematicians define appropriate regions of integration and ensure accurate calculations.III. Asymptotes in Statistics (300-400 words):Asymptotes also have significant applications in statistics, particularly when dealing with probability distributions. Many commonly used probability distributions exhibit asymptotic behavior. Two types of asymptotes are particularly relevant:1. Horizontal Asymptotes:In probability distributions, a horizontal asymptote represents the limit of the distribution as the number of observations or sample size tends to infinity. This behavior is often observed in the case of central limit theorems, where the sum of a large number of random variables tends to converge towards a specific distribution.2. Asymptotic Efficiency:In statistics, the concept of asymptotic efficiency compares the efficiency of different estimation procedures, particularly in large sample sizes. This efficiency is often measured by examining the limit behavior of estimators, such as unbiasedness or consistency.Conclusion (150-200 words):Asymptomatic, while seemingly abstract and perhaps intimidating, plays a fundamental role in understanding the behavior of mathematical functions and sequences. From calculus to statistics, this concept finds valuable applications and helps mathematicians and statisticians model natural phenomena, make predictions, and draw meaningful conclusions. By grasping the various types of asymptotes and their significance in different areas of mathematics, researchers can unlock new opportunities for analysis and continue to probe the intricacies of the mathematical world. So, the next time you encounter an asymptote, marvel at the beauty of this concept and appreciate its fundamental contribution to our understanding of the world around us.。
Empirical processes of dependent random variables
2
Preliminaries
n i=1
from R to R. The centered G -indexed empirical process is given by (P n − P )g = 1 n
n
the marginal and empirical distribution functions. Let G be a class of measurabrocesses that have been discussed include linear processes and Gaussian processes; see Dehling and Taqqu (1989) and Cs¨ org˝ o and Mielniczuk (1996) for long and short-range dependent subordinated Gaussian processes and Ho and Hsing (1996) and Wu (2003a) for long-range dependent linear processes. A collection of recent results is presented in Dehling, Mikosch and Sorensen (2002). In that collection Dedecker and Louhichi (2002) made an important generalization of Ossiander’s (1987) result. Here we investigate the empirical central limit problem for dependent random variables from another angle that avoids strong mixing conditions. In particular, we apply a martingale method and establish a weak convergence theory for stationary, causal processes. Our results are comparable with the theory for independent random variables in that the imposed moment conditions are optimal or almost optimal. We show that, if the process is short-range dependent in a certain sense, then the limiting behavior is similar to that of iid random variables in that the limiting distribution is a Gaussian process and the norming √ sequence is n. For long-range dependent linear processes, one needs to apply asymptotic √ expansions to obtain n-norming limit theorems (Section 6.2.2). The paper is structured as follows. In Section 2 we introduce some mathematical preliminaries necessary for the weak convergence theory and illustrate the essence of our approach. Two types of empirical central limit theorems are established. Empirical processes indexed by indicators of left half lines, absolutely continuous functions, and piecewise differentiable functions are discussed in Sections 3, 4 and 5 respectively. Applications to linear processes and iterated random functions are made in Section 6. Section 7 presents some integral and maximal inequalities that may be of independent interest. Some proofs are given in Sections 8 and 9.
计量经济学中英文词汇对照
Common variance Common variation Communality variance Comparability Comparison of bathes Comparison value Compartment model Compassion Complement of an event Complete association Complete dissociation Complete statistics Completely randomized design Composite event Composite events Concavity Conditional expectation Conditional likelihood Conditional probability Conditionally linear Confidence interval Confidence limit Confidence lower limit Confidence upper limit Confirmatory Factor Analysis Confirmatory research Confounding factor Conjoint Consistency Consistency check Consistent asymptotically normal estimate Consistent estimate Constrained nonlinear regression Constraint Contaminated distribution Contaminated Gausssian Contaminated normal distribution Contamination Contamination model Contingency table Contour Contribution rate Control
Hilbert空间中由Rosenblatt过程驱动的带有限延迟的随机发展方程
Hilbert空间中由Rosenblatt过程驱动的带有限延迟的随机发展方程桑利恒;吕文华;唐正【摘要】Rosenblatt过程作为一个重要的自相似随机过程,常被用来刻画非高斯随机现象.为进一步研究Rosenblatt过程对随机现象的刻画,本文考虑由Rosenblatt 过程驱动的带有限延迟的一类时间相依随机发展方程适度解的问题.在实值可分Hilbert空间中,运用Banach不动点定理得到了Rosenblatt过程驱动的带有限延迟的随机发展方程适应解的存在性和唯一性,并通过例子说明所得结果是有效的.【期刊名称】《工程数学学报》【年(卷),期】2019(036)003【总页数】13页(P309-321)【关键词】随机发展方程;发展算子;Rosenblatt过程;不动点定理;适度解【作者】桑利恒;吕文华;唐正【作者单位】滁州学院数学与金融学院,安徽滁州 239000;滁州学院数学与金融学院,安徽滁州 239000;安徽师范大学数学与统计学院,安徽芜湖 241000【正文语种】中文【中图分类】O211.631 引言自相似过程,作为统计上的一种随机过程,由于它在时间和空间中具有不变性,被广泛应用于网路流量分析、数量金融、天体物理学、水文、图像处理等领域.在概率论中,自相似过程作为随机分析的重要研究内容,也得到了深入的研究,如Dobrushin 和Major[1]、Taqqu[2]等研究了一类有趣的自相似过程,并得到了非中心极限定理.下面简要回顾一些与自相似相关的知识.设(ξn)n∈N 为一个均值为0、方差为1 的平稳高斯序列,且相关函数满足其中H ∈(,1),L 为n 趋于无穷时的慢变函数.令g 为k 阶Hermite 函数,即,若g 能展开成如下的Hermite 多项式那么k=min{j|cj ≠0}≥1,其中Hj(x)为Hermite 多项式,其表达式为那么,由非中心极限定理可得:当依有限维分布收敛于如下随机过程式中的积分是关于标准布朗运动{B(y)}y∈R 的 k 重 Wiener-Itˆo 积分,c(H,k)>0 为依赖于H 和k 的常数.过程{ZkH(t)}t≥0 称为Hermite 过程,且具有平稳增量性和H 自相似性,即满足众所周知,对于Hermite 过程(1),当k=1 时,它为分数布朗运动.当k=2 时,它为Taqqu[3]定义的Rosenblatt 过程,但它不是高斯的.在Hermite 过程的众多研究中,关于分数布朗运动过程的研究颇多,这主要是由于分数布朗运动的广泛应用.事实上,分数布朗运动的广泛应用主要源于Hermite 过程的自相似性、平稳增量性和长相依性[4]这三种性质.同时,又由于分数布朗运动为高斯过程,易于计算,使得一些学者更偏爱运用分数布朗运动来刻画事物的随机现象.然而在现实中,并不是所有的随机现象都具有高斯性.当研究现象不具有高斯性时,我们就需要运用如Rosenblatt 过程等非高斯过程对事物的随机现象进行刻画.关于Rosenblatt 过程,目前有许多学者分别从不同角度对其进行了深入的研究.如,Albin[5]研究了Rosenblatt 分布的极值性质.Leonenko 和Ahn[6]通过非中心极限定理得到了Rosenblatt 过程的收敛速度.Abry 和Pipiras[7]给出了Rosenblatt 过程的小波发展.Tudor[8]建立了有限区间上Rosenblatt 过程关于布朗运动的Wiener-Itˆo 多重积分表达式,并且给出了相应的随机积分.关于Rosenblatt 过程的更多研究,可参见文献[9,10].近年来,许多学者也对维纳过程驱动的随机发展方程进行了研究.如Da Prato 和Zabczyk[11]等.进而,在许多科学领域,众多学者对具有记忆性或后效性的系统(即在状态方程中具有有限延迟的系统)也产生了浓厚兴趣.因此,有必要研究具有有限延迟的随机发展方程.关于这方面的工作,可参见文献[12–14]等.近期,不同随机过程驱动的随机发展方程得到了广泛的关注,并获得了很好的结论[15].特别地,很多学者研究了Hilbert 空间中由分数布朗运动驱动的随机发展方程[16-19].然而,目前由Rosenblatt 过程驱动的带延迟的时间相依的随机发展方程鲜有人进行研究.基于先前对其它随机过程驱动的发展方程的研究工作,本文将在实值可分Hilbert 空间U 中考虑由Rosenblatt 过程驱动的带有限延迟时间相依的随机发展方程其中D 是U 的稠密子集,A(t):D ⊂ U → U,t∈J,是定义在D 上的稠密闭线性算子,且满足Acquistapace-Terreni 条件(简称ATC),并生成一个强发展算子U(s,t),0 ≤t≤s≤T.若令(K, ·K,〈·,·〉K)为另一个实可分Hilbert 空间,则 ZQ(t)为K 值的Q-Rosenblatt 过程.设T≥0 为固定实数,令(Ω,F,P)为完备的概率空间,并且对t≥0,Ft 为由{ZQ(s),s ∈ [0,t]}和P 零测集生成的σ-域.令L(K,U)为由 K到U 的有界连续线性算子生成的空间.f:[0,T]×U →U 和σ:[0,T]→LQ(K,U)为两个适当的映射(在后文中将明确规定),其中LQ(K,U)记为由K 到U 的所有Q-Hilbert-Schmidt 算子空间,我们将在下节中给出它的定义.延迟函数r:[0,+∞)→[0,τ]是连续的.初始值ϕ={ϕ(t):−τ≤t≤0}是一个二阶矩有限且独立于Rosenblatt 过程ZH 的F0-可测的随机过程.本文的主要工作是运用Banach 不动点定理证明方程(2)适度解的存在性和唯一性.最后给出一个例子来说明这个定理是有效的.2 预备知识本节,我们给出一些证明定理所需要的基础知识和记号.用L2(Ω,U)表示平方可积的U-值随机变量x 的空间,即并记易知L2(Ω,U)是具有范数·2 的Hilbert 空间.记L(K,U)表示由K 到U 的所有有界线性算子空间,当U=K 时,此空间简记为L(K),并记Q ∈L(K)为非负自共轭算子.设K0 为任意一个可分的Hilbert 空间,=L2(K0,U)为关于Hilbert-Schmidt 范数的可分Hilbert 空间.(K,U)为所有使得为 Hilbert-Schmidt 算子的ψ ∈L(K,U)构成的空间,其范数为其中ψ 称为由 K 到 U 的Q-Hilbert-Schmidt 算子.记(Ω,U)表示 U-值F0-可测的平方可积随机过程空间.2.1 Rosenblatt过程下面给出Rosenblatt 过程的一些基础知识.对于任意固定常数T,考虑时间区间[0,T],设{ZH(t),t ∈ [0,T]}为具有参数H的一维Rosenblatt 过程.根据文献[8],参数为H > 的Rosenblatt 过程可表示为其中Γ(·,·)为 Beta 函数,{B(t),t ∈ [0,T]}为布朗运动,Rosenblatt 过程{ZH(t),t ∈ [0,T]}的协方差为Rosenblatt 过程的协方差结构使我们能够构造出关于它的维纳积分.关于一般的Hermite过程的维纳积分可参见文献[20],更一般的情况可参见文献[8,21].注意到其中I 为定义在函数f:[0,T]→R 的集合上,取值于函数g:[0,T]2 →R2 的集合上的算子,其表达式为设f 为[0,T]上形如下式的阶梯函数所生成的集合E 的元素进而,f 关于ZH 的维纳积分可定义为令由文献[8],有Maejima 和Tudor[20]已经证明了映射定义了一个由到L2(Ω)的等距同构.同时,由于为H 中的稠密集,所以这个映射可以继续推广为到L2(Ω)的等距同构.这种推广称为f ∈H 关于ZH 的维纳积分.注意到空间H 不仅包含了函数,而且它的元素也可以为分布.因此,可以定义H 的子空间虽然,空间|H|关于范数·H 是不完备的,但关于范数却是完备的赋范线性空间—Banach 空间.因此对任意的f ∈L2([0,T]),可得和其中常数C(H)>0.为简便起见,本文记C(H)>0 为仅依赖于H 的正常数,并且它的值在不同的位置可以不相同.定义由E 到L2([0,T])的线性算子为其中K 为(3)式表示的Rosenblatt 过程的核函数,并且注意到所以算子是由E 到L2([0,T])等距同构,并且它能够被延拓到希尔伯特空间H中.即,对任意的s,t ∈[0,T],有此外,对于f ∈H,我们有下面考虑一个K-值随机过程ZQ(t)序列其中{zn(t)}n∈N 为定义在(Ω,F,P)上相互独立的一维双边Rosenblatt 过程序列.若Q 是一个非负自共轭迹类算子,则这个随机过程ZQ(t)序列在空间K 中是收敛的,即有ZQ(t)∈L2(Ω,K).从而,过程ZQ(t)是一个具有协方差算子Q 的K-值Q-Rosenblatt过程.例如,假设Q 是K 中的核算子,若{σn}n∈N 是一个非负有界实数序列并满足Qen=σnen,则随机过程是 K-值 Q-Rosenblatt 过程.定义1[4] 假设φ:[0,T]→(K,U)满足那么,其关于Rosenblatt 过程ZQ(t)的随机积分可以定义为:对t≥0,有引理1[19] 设ψ:[0,T]→(K,U)满足对任意a,b ∈[0,T],b>a,有对于t ∈ [0,T],若是一致收敛的,则有引理2 若映射σ:[0,T]→(K,U)满足发展族U(t,s)是以指数稳定的,即存在两个常数M≥1 和δ >0,使得对t≥s,均有则从而得随机积分是有意义的.证明假设{en}n∈N 是K 的完备正交基,则2.2 发展算子在定理证明中,要用到Acquistapace 和Terreni[22,23]中如下发展算子的知识.引理3 假设{A(t),t ∈J}是闭的线性算子族,满足Acquistapace-Terreni 条件,即存在常数L0 >0,α1,α2,···,αk,γ1,γ2,···,γk,0≤γi <αi≤2,i=1,2,···,k,使得对s,t ∈ R,λ ∈ Sθ\{0},有其中并且存在一个常数L1≥0,使得则存在唯一的发展族{U(t,s),−∞<s ≤t},满足:(i)U(t,s)U(s,r)=U(t,r);(ii)对实数r≤s≤t,有U(t,t)=I;(iii)对于t>s,(t,s) →U(t,s)是连续的;(iv)对于0<t−s≤1,k=0,1,有注1 若A(t),t≥0,是二阶微分算子A,即对每个t≥0 有A(t)=A,则A 可生成一个C0-半群{eAt,t≥0}.2.3 定义和假设下面给出方程(2)的适度解定义,并记J=[0,T].定义2 如果连续的随机过程x:[−τ,T]→U满足:(i)x(t)∈ C([−τ,T],L2(Ω,U)),由[−τ,T]到L2(Ω,U)的具有上确界范数的所有连续函数所组成的Banach 空间;(ii)x(t)=ϕ(t),− τ≤t≤0;(iii)对于每个t ∈J,x(t)满足如下积分方程那么,称x 是(2)的适度解.本文将在如下假设条件下开展研究:(H1):发展族U(t,s)是以指数方式稳定的,即存在两个常数M≥1 和δ >0,使得对任意t≥s,均有(H2):映射f:J ×U →U 是可测函数,并且存在两个正常数C1 和C2,使得对所有的t ∈ J,ϕ,ψ ∈ U,均有(H3):映射σ:J → 满足:存在一个正常数L,使得在 J 上一致成立.3 适度解的存在性和唯一性在本节中,我们运用Banach 不动点定理得到方程(2)适度解的存在性和唯一性定理.主要结果如下:定理1 假设(H1)–(H3)成立,以及x0 ∈L2(Ω,U).如果则在[−τ,T]上,方程(2)存在唯一的适度解.证明给定T >0,设CT:=C([−τ,T],L2(Ω,U)),其上确界范数定义为且则ST(ϕ)是范数为·CT 的CT 的闭子集.定义ST 上的算子Γ 为由第2 节,我们知道:对每个t ∈J,Γ(x)(t)是一个随机过程,那么证明方程(2)适度解的存在性和唯一性等价于寻找算子Γ 的不动点.接下来,我们将运用Banach 不动点定理证明算子Γ 具有不动点.为此,我们分两步进行:步骤1 对任意的x ∈ST(ϕ),我们将证明t →Γ(x)(t)在区间[0,T]上是L2(Ω,U)意义连续的.假设0<t<T,|h|是充分小的数,则对任意固定的x ∈ST(ϕ),有根据引理3,得由(H1),得因此,由Lebesgue 控制收敛定理,可得对于I2(h),我们考虑h>0 的情况(对于h<0,可应用类似的方法得到结果)对I21(h)项,有由引理3,得和因此,通过Lebesgue 控制收敛定理,得到对于I22(h)项,根据(H1),(H2)和不等式,得进而得对于I3(h),我们有对于I31(h)项,通过引理1 和(H3),有根据引理3,得到由Lebesgue 控制收敛定理,可得再一次运用引理1,得从而综合上述讨论,可得因此,映射t →Γ(x)(t)在区间[0,T]上是L2(Ω,U)-意义连续的.步骤2 我们将证明映射Γ 是ST(ϕ)上的压缩算子.对x,y ∈ ST(ϕ)和t ∈ [0,T],我们有根据 Hlder 不等式和 (H2),可得从而,得其中由(6)式,我们得到Γ 是ST(ϕ)上的压缩映射.因此,算子Γ 具有唯一的不动点.4 例子下面将给出一个例子来说明本文所得结论的有效性.例1 考虑由Rosenblatt 过程驱动的具有有限延迟的如下随机偏微分方程其中ZQ(t)为定义在完备概率空间(Ω,F,P)上的参数为H ∈(,1)的Rosenblatt 过程.为了能够把方程(7)写成方程(2)的形式,我们考虑空间U=L2([0,π]),定义算子A:D(A)⊂U →U,它满足Az=z′′,D(A)={z ∈ U,z,z′ 是绝对连续的,且z′′ ∈ U,z(0)=z(π)=0},则A 是U 上解析半群{S(t)}t≥0 的无穷小生成元.A 具有离散频谱,其特征值为−n2,n ∈N,相应的标准化特征函数为且{en,n ∈N}是U 的正交基.接下来,定义算子A(t):D(A)⊂H →H,且假设b(·)是连续的,若对每个t ∈ R,有b(t,ξ)≤ −γ (γ >0)成立,那么有发展族由上述的表述,可得U(t,s)是以指数方式稳定的,并且对每个t,s ∈J,t >s,有U(t,x)≤e−(1+γ)(t−s).设v(t)(·)=v(t,·),t ∈ J,我们定义f(t,v)(·)=F(t,v(·)),则方程(7)能表示为方程(2)的形式.进而,如果在F 上施加适当的条件去验证定理1 的条件,我们可得到方程(7)在J 上具有唯一的适度解.参考文献:【相关文献】[1]Dobrushin R L,Major P.Non-central limit theorems for non-linear functional of Gaussian fields[J].Zeitschrift fr Wahrscheinlichkeitstheorie und Verwandte Gebiete,1979,50(1):27-52 [2]Taqqu M.Convergence of integrated processes of arbitrary Hermite rank[J].Zeitschrift fr Wahrscheinlichkeitstheorie und Verwandte Gebiete,1978,50(1):53-83[3]Taqqu M.Weak convergence to the fractional Brownian motion and to the Rosenblatt process[J].Zeitschrift fr Wahrscheinlichkeitstheorie und VerwandteGebiete,1975,31(4):287-302[4]Tindel S,Tudor C A,Viens F.Stochastic evolution equations with fractional Brownian motion[J].Probability Theory and Related Fields,2003,127(2):186-204[5]Albin J M P.On extremal theory for self similar processes[J].Annals ofProbability,1998,26(2):743-793[6]Leonenko N N,Ahn V V.Rate of convergence to the Rosenblatt distribution for additive functionals of stochastic processes with long-range dependence[J].Journal of Applied Mathematics and Stochastic Analysis,2001,14(1):27-46[7]Abry P,Pipiras V.Wavelet-based synthesis of the Rosenblatt process[J].Signal Processing,2006,86(9):2326-2339[8]Tudor C A.Analysis of the Rosenblatt process[J].ESAIM Probability andStatistics,2006,12:230-257[9]Chen C,Sun L,Yan L.An approximation to the Rosenblatt process using martingale differences[J].Statistics & Probability Letters,2012,82(4):748-757[10]Shen G,Ren R.Neutral stochastic partial differential equations with delay driven by Rosenblatt process in a Hilbert space[J].Journal of the Korean StatisticalSociety,2015,44(1):123-133[11]Da Prato G,Zabczyk J.Stochastic Equations in InfiniteDimensions[M].Cambridge:Cambridge University Press,1996[12]Mao X.Stochastic Differential Equations and Applications[M].Chichester,UK:Horwood Publishing,1997[13]Hu L,Ren Y.Existence results for impulsive neutral stochastic functional integro-differential equations with infinite delays[J].Acta ApplicandaeMathematicae,2010,111(3):303-317[14]Luo J,Liu K.Stability of infinite dimensional stochastic evolution equations with memory and Markovian jumps[J].Stochastic Processes and theirApplications,2008,118(5):864-895[15]Chen Z Q,Zhang T.Stochastic evolution equations driven by L´evy proecesses[J].Osaka Journal of Mathematics,2011,48(2):311-327[16]Boufoussi B,Hajji S.Neutral stochastic functional differential equations driven by a fractional Brownian motion in a Hilbert space[J].Statistics & ProbabilityLetters,2012,82(8):1549-1558[17]Caraballo T,Diop M A.Neutral stochastic delay partial functional integro-differential equations driven by a fractional Brownian motion[J].Frontiers of Mathematics in China,2013,8(4):745-760[18]Maslowski B,Nualart D.Evolution equations driven by a fractional Brownianmotion[J].Journal of Functional Analysis,2003,202(1):277-305[19]Ren Y,Cheng X,Sakthivel R.On time-dependent stochastic evolution equations driven by fractional Brownian motion in a Hilbert space with finite delay[J].Mathematical Methods in the Applied Sciences,2014,37(14):2177-2184[20]Maejima M,Tudor C A.Wiener integrals with respect to the Hermite process and a non central limit theorem[J].Stochastic Analysis and Applications,2007,25(5):1043-1056 [21]Kruk I,Russo F,Tudor C A.Wiener integrals,Malliavin calculus and covariance measure structure[J].Journal of Functional Analysis,2007,249(1):92-142[22]Acquistapace P,Terreni B.A unified approach to abstract linear nonautonomous parabolic equations[J].Rendiconti del Seminario Matematico della Universitàdi Padova,1987,78(2):47-107[23]Acquistapace P,Terreni B.Initial boundary value problems and optimal control for nonautonomous parabolic systems[J].SIAM Journal on Control andOptimization,1991,29(1):89-118。
第八章中心极限定理
自从高斯指出测量误差服从正 态分布之后,人们发现正态分布在 自然界中极为常见。
观察表明,如果一个量是由大量相互独 立的随机因素的影响所造成,而每一个别因 素在总影响中所起的作用不大。则这种量一 般都服从或近似服从正态分布。
• 一般地,在研究许多随机因素产生的总影响 时,很多可以归结为研究相互独立的随机变 量之和的分布问题,而通常这种和的项数都 很大。因此,需要构造一个项数越来越多的 随机变量和的序列: ZX 1X 2X n
t2
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对于均值为 方, 差 2的0独立同分布的 l.v 列
有 即或
X1,X2,,Xk,
n
~ Xk n 近似
k 1
n
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~ X 1 + X 2 + X n 近似 N (n,n2 )
在实际问题中,如果某数量指标满足
该指标是由大量相互独立的随机因素迭加而成
这些随机因素都是微小的、没有一个因素起到
k
O 1 2 3 4 5 6 7 8 9 10 11
高尔顿( Francis Galton,18221911) 英国人类 学家和气象学家
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记
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小球碰第 k 层钉后向右落下 小球碰第 k 层钉后向左落下
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注: 此为林德贝尔格-勒维定理的特殊情况。
该定理是概率论历史上第一个中心极限定理,由棣莫弗于1730 年给出p=1/2 时的证明,几十年后经拉普拉斯推广到0<p<1 的一般情形.
对于一列二项分布r.v n~b (n ,p )( ,n有 1 ,2 ,)
SCI论文摘要中常用的表达方法
(3)介绍应用、用途,常用词汇有use, apply, application等
结果部分
(1)展示研究结果,常用词汇有show, result, present等
(2)介绍结论,常用词汇有summary, introduce,conclude等
讨论部分
(1)陈述论文的论点和作者的观点,常用词汇有suggest, repot, present, expect, describe等
(2)说明论证,常用词汇有support, provide, indicate, identify, find, demonstrate, confirm, clarify等
SCI摘要引言部分案例 attention
SCI摘要方法部分案例 consider
SCI高被引摘要引言部分案例 词汇outline
? Author(s): TIERNEY, L SCI引用728次
引言部分 回顾研究背景常用词汇summarize
Abstract: This biennial review summarizes much of Particle Physics. Using data from previous editions, plus 1900 new measurements from 700 papers, we list, evaluate, and average measured properties of gauge bosons, leptons, quarks, mesons, and baryons. We also summarize searches for hypothetical particles such as Higgs bosons, heavy neutrinos, and supersymmetric particles. All the particle properties and search limits are listed in Summary Tables. We also give numerous tables, figures, formulae, and reviews of topics such as the Standard Model, particle detectors, probability, and statistics. A booklet is available containing the Summary Tables and abbreviated versions of some of the other sections of this full Review.
4. Central Limit Theorem
Sampling Distribution of Sample MeansA sampling distribution of sampling means is a distribution obtained by using the means computed from random samples of a specific size taken from a population.Sampling ErrorSampling error is the difference between the sample measures and the corresponding population measure due to the fact that the sample is not a perfect representation of the population.Properties of the Distribution of Saample Mean1.The mean of the sample means will be the same as the population mean.2.The standard deviation of the sample means will be smaller than the standard deviation of the population, and it will be equal to the population standard deviation, divided by the square root of the sample size.Formula1.μμμμ==∑=X X n X2.n X σσ=The Central Limit TheoremAs the sample size n increases, the shape of the distribution of the sample means taken from a population with mean μand standard deviation σwill approach a normal distribution. This distribution will have mean μand a standard deviationn σ. The z-values are computed as : n X z /σμ-=Finite Population Correction FactorSince most samples are drawn without replacement from a finite population, a correction factor is used.1--N nNWhen the sample size n is greater than 5% of thepopulation size N, the finite correction factor is used to correct the standard error of the mean.1--⋅=N n N nX σσ The formula for computing the z-value is:1--⋅-=N n N nX z σμThe Normal Approximation To The Binomial DistributionCondition: 5≥np and 5≥nqA correction for continuity is a correction employed when a continuous distribution is used toapproximate a discrete distribution.()()()()()()()()5.455.775.085.0885.05.0≥=≥≤=≤+≤≤-==+≤≤-=X NP X BP X NP X BP X NP X BP k X k NP k BPProcedure for the Normal Approximation to theBinomial Distribution1.Check to see whether the normal approximation can be used.2.Find the mean npμand the standard deviation npq.=3.Write the problem in probability notation, using X.4.Rewrite the problem by using the continuity correction factor, and show the corresponding area under the normal distribution.5.Find the corresponding z-values.6.Find the solution.。
【STATA】面板数据如何处理异方差
【STATA】⾯板数据如何处理异⽅差⼀、前⾔ 计算和互联⽹技术的⼴泛运⽤极⼤地提⾼了数据的可获得性,使⼤量的数据得以收集、保存和整理。
与此同时,计量经济学在整个经济学体系中的地位⽇益提升。
在顶级经济学杂志的论⽂中,应⽤计量论⽂已占到了相当⾼的⽐例。
正是在这些背景之下,⾯板数据受到了越来越多经济研究⼈员的欢迎,⾯板数据的应⽤研究亦成为热点。
⾯板数据成为研究的热点⼀⽅⾯⾃然是因为本⾝优秀的特质;另⼀⽅⾯也归因于⾯板数据在应⽤过程中仍有许多问题和未知领域需要去探索。
在⾯板数据回归分析中,如果存在异⽅差,最⼩⼆乘估计出的系数尽管是线性、⽆偏和⼀致的,但不是有效的,甚⾄不是渐进有效的。
这些影响将导致参数估计和假设检验失效。
⼆、异⽅差产⽣的原因 异⽅差产⽣的因素很多,⽐如模型中省略了某些重要的解释变量,模型形式设定不准确,样本数据中存在的测量误差,异常值的出现,截⾯个体之间的差异等。
⾯板数据是具有时序和截⾯双重性质的数据形式,异⽅差不仅会出现在时间序列上还将出现在横截⾯序列上,所以⾯板数据模型中的异⽅差问题要⽐单纯的时间序列或截⾯数据模型要复杂得多。
三、⾯板数据异⽅差处理⽅法 实际上,在处理⾯板数据线性回归时,主要考虑固定效应模型与pooled OLS的异⽅差问题。
因为随机效应模型使⽤GLS估计,本⾝就已经控制了异⽅差。
Huber (1967)、Eicker (1967) 和 White (1980)提出了异⽅差—稳健⽅差矩阵估计,该⽅法能够在考虑异⽅差情况下求出稳健标准误。
利⽤异⽅差稳健标准误对回归系数进⾏t检验和F检验都是渐近有效的。
这就意味着,如果出现异⽅差,仍然可以使⽤OLS回归,只需结合使⽤稳健标准误即可。
在STATA中,异⽅差—稳健标准误可以在“reg”或者“xtreg”语句后,加选择性命令“robust”即可得到。
但是这⼀⽅法有⼀个假设的前提:残差项是独⽴分布的。
Parks(1967)提出了可⾏⼴义最⼩⼆乘法(FGLS),⼀般⽤于随机效应模型估计。
【doc】经验过程的Cesaro大数定律
经验过程的Cesaro大数定律第2O卷第2期1998年6月V0l-2ONo.2Jun.1998经验过程的Cesaro大数定律刘吉定(基础教育部)摘要得到了经验过程的Cesaro大数定律成立的充要条件.设X为概率空间(/-/,,P)上取值于可涮空间(s,)中的随机元,{x).为x的独立版本序列.在给予,一可测函数族以某些条件下,对所有∈(O,1),得到Il{蚱l,(墨)一0,a.s.……/怅P艮定弭关键词赋范空间的随机元;经验过程;独立随机元的和外ft1分类号O231.41引言和主要结果可分B值随机元的某些重要极限定理在经验过程中已有相应的形式.例如,Ledoux,M.和Talagrand,M建立了经验过程的LIL;吴黎明教授建立了经验过程中另一形式的LIL;Dudley开创了经验过程的CLT的课题0;邵启满和于浩研究了配重经验过程的收敛性问题.本文建立了可分B空间的Cesaro大数定律在经验过程中的相应形式.设(n,,P)是一概率空间,(s,)是一可测空间,x为(n,,P)上取值于(s,)中的随机元.不妨设(n,,尸)足够大,其上存在x的独立版本序列{X}≥.,{X)≥o的独立版本{x}.≥.以及与{X},{X)≥.独立的Bernoulli序列}≥o,管是S上的一族实值一可测函数.对于任何以管为下标集的一族实值{4,},,记d,川一supI,I.令盘一{—哝的映射,supI(,)l<..}.V,yE盘,令(Xx+蚶)(,)一Xx(f)+(,),V,∈雪.则盘为一线性空间,这样,(盘,I)为一赋范空间.本文中,表示只与有关的常数,在不同的地方,它有可能表示不同的常数.为在可测条件下讨论,还设管只含可数个函数.定理设V,∈管,El(X)一0?{ll白'A:二:).£|If(X)l1,2}(EN)I~-Pr?Vz∈S1If(x)<..(1)则对于任何∈(0,1),有1lill∑A:ZIf(X)=0,a.s.(2)~一成立的充要条件是zllf(x)<oo.(3)收稿日期{1997—1O一27刘吉定:男,1963年生?硕士,讲师武汉化工学院第2O卷2几条引理及其证明为了证明定理,需要下面几条引理;引理1且:一∑A:,~/r(+1)(文献[6],P.42).…引理2设{.)是一值独立随机元列,{目)是实数列,V,∈,i一1,2,…,EI/(x,)<o.,则Vt>0,n∈N,有P{∑m(,(墨)一Ef(X))>3t}一I≤2P{1_,(I>f}+~…upp{IZ(,(x)_E,(墨))l>)?证明由文献[7]可知:Vt>0,n∈N,有(卜s脚upP{I~n(,(墨)一Ed(X.))l>£训(,(墨卜Ef(x>3)≤尸钏(,()一,(,))l_>2}故,对任何一4-1,k一1,2,…,n,有P钏(,()一Ef(X))l_>3t}≤P{f1,(一f(X-}-supP{1,(墨)_E,')1>)一E{l_(,(墨卜f(xI1>2¨+supP{1,(墨卜E,(墨))1>}<ze{ilZ…f(X>}+s脚upP{I,(一E,(XD)I>}?引理3([8]P.165)设{}是—值独立随机元列,{4,)是实数列,p>O,V,∈, Elf(x)I>oo,则,,n∈N,圳e,(驯1≤4.3m—axII:C,n,(驯I;+16'3}这里:inf[z>o:P{II~f(x,)11>}≤i_南]引理4([8]P.164)设(x_.'X)是一值独立随机元组,(n..'口)是实数组,Vf6, ,(五)(1≤i≤n)对称,则Vt>O,有P{I1f(x>3£}≤P{.s"upIIf(xr)11>£}+4Pa{.?,(驯1>)引理5([9]Th.2.1)设(.-'x)是一值独立随机元,(n")是实数组.若存在M >o,使得V1,2,…,n,IIf(X,)≤'a.s.定义一EllnJf(x.),则V>o,有P({I1n,,(x.)l1一Elln,,(x)l>£}≤2exp{南一(南+南)ln(1+)}.引理6设VxES,1If(x)<co,{.)是一值独立同分布随机元列,Vf6,≥O, f(.)对称,若第2期刘吉定:经验过程的Cesaro大效定律891Im∑=if(x)11一o,a.s~~则EIIf(Xo)<...证明对每一个整数,定义g?一f(X?)",(I){{1(4)(5)令Gl一去A:=l,由对称性及L∈vy不等式,可得存在>o,使得su≥p.P{nIIA:二j,(x)11>)≤吉从而infIn(P{supIIA'~:if(X)≤M})≥一1n2】nH0《^≤所以P{蚱If()11>)≤ln2因此存在常数使得sup[:尸{k.-Ln~IIf(x.)>KM}+P{n_IIf(X.)>KM}]≤In2…^一l于是sup(n+1)P{II/(Xo)>KMn)≤ln2由此可得suptP{IIf(x.)>t)<..(6)由(6)式及BorelCantelli引理,即有liraIIGI一0,a.S.(7)定义"0一go,"】一g1一g一,"^一--g,…,NV≥O,g一"0+"l+…+.令g是舅的共轭空间舅的单位闭球中的一个元素,对每一个∈(<..},定义s()一s(,m)如下:1,1)及每一个∈{:lIGl()一∑(1一)一g(ua)一∑(1一)一'(∑)g(机)●≥0≥0J≥^由IIII≤可知s()一∑一(1一)一'(∑g(u))一∑(1一)一g(gj)J≥0o~t<jo∑一(∑A:一')g(g)∑Agg(G,)V∞∈{甜:pG一(∞)<..},V∈(一1,1)g∑∑培∑∑一A∑∑g一一A∑∑Ⅲ一得正而从90武汉化工学院第2O卷F()垒[∑g(u)](∞)一(1一)[∑(Gt)])垒G)显然,F,G在(一1,1)内的每一点有相同的任意阶导数.由引理1可知V,Ig(u.m){<肼supG)ll由(7)式得sUPlIG<oo,a.s.所以,由{}的独立性便可知∑P{Ilu.>Kn~}<oo由(5),(6)及(10)式可知∑P{IIf(X)一f(x)11>Kn}n≥1≤∑P{IIf(X)>()}+∑P{llf(x2n-I)11>(2一1)}n≥1I≥1+∑P{Ilu)11>Kn"}<o..由(11)式,Fubini定理及lIf(x)<oo(V∈S)可知EIIf(X.)≤EIIf(X)一f(x.)<oo.3主要定理的证明充分性首先证明客A==..由引理2可得V e>O,有P哇ll蚱{朋3e}≤2P{∑蚱{f(x)II>e}+~upe{^1k'I--0…'由引理1及文献[1]之定理5可得(8)(9)(10)(11)(12)>e}.(13)P{杀∑:=:e,(x)II>e}≤(+1)P(1lf(X.)ll>e)+筹Ell∑(蚱:)If(Xt)(IJ'cxj)ll~4II一(14)由引理3可得supElI(蚱:If(X,)(1,,IIup'12EmaxIIf(X)II1'I_l,}十sup>fll骞(蚱e.,({『^}II>£}≤](15)由经典手法([1OJ,P331),可知P(1I∑(以:二:)If(X?)II《Ifc.)}『≤^?1I1+>.}^tUX,A∑~第2期刘吉定:经验过程的Cesaro太散定律91≤2P{∑(A:=i)If(x)l>n'/Zt)_n(16)由{(A:二:)".£Jl,(五)I.z)-e随机有界,(15),(16)式及引理,可得.upEll∑(A:=If(x)11/qc.?≤K(17)对£≤1一致成立.由EIIf(X.)<..及(14),(17)式立即得到--*∑k=oA:=:f(X?)110?'下面考虑(13)式右边第二项.由Chebyshev不等式,比较原理(文献[10],P.141'~1理3)及引理3可得sup尸(}骞蚱:似)I>24supE(.max,A~=ilf(X,)1)+96sup.(,)(1g)这里(,)=inf[>0:P(1A:二:£jf(X)l>)<].由EIIf(X.)lI<oo,不难得到~E(max[If(X))一0(∞由引理1,Jensen不等式及(20)式,可得;EA:=ll,(托)1)≤音E',(噩)咿)).一.(一..'由于}1∑A.a一-If(X)11,(n~OO).故v>0,当"》1时P{蚱:£jf(X,)ll>)<月^0O从而,当》1时,有屯(,)≤A:a.由(19),(21)及前式可得lirasupP{~I蚱i,(I>E)_0(2)由式(13),(18)及(22)可得式(12).由(12)式及经典的对称化手法(文献[11]P.159及[12]Lemma2.2)可知,为证(2)式,须证明limll士∑A:=i(,(五)一f(X?))一0,a.s.即只须证明:若{,(x.)).≥.(,∈管)是i.i.d.对称随机变量列,使得EIIS(X.)<..,则limll击∑A:=:,(五)11一0,a.s.(23)由EIIS(X.)ll<..可知:存在一串单调下降到0且属于(0,1)的数{),满足∑P(IIS(X)>口< (24)1定义V≥0,f(Y^)垒,(x^)I九)l,};V"≥0,Wn垒台A:二l,(y^)-由(24)及Borel—Cantelli引理可知:为证(23)式,只须证明limllW.1I=0a.s为此先证明!EI1w一一0-由引理1及引理4得V≥0,t>O,有(25)92武汉化工学院第2O卷P{IIW>.[丢(+…>)号故'有,∈(÷,1)P圳u,II>3}≤inf(1,K)£一~EIIfCX.)ll)+4P{IIW>},(26)由于随机映射f(Y)是有界的,故u,是可积的.首先选择t0=()>0使得P{l1w>} <?由(26)式可得ElIW一3IP{lIW>3I}dr≤3Jinf(1,K)t-÷E1l,(ll£+2+专』:Plllw>}}d£≤3j:d蚪3j二.KEIIfCX.)lI")t-l/,dt+~EIIW-II+24由此可得EtLw≤6n+6K?丁Eiif(X.)哆)一+48t.,(27)据(12)式,能选")使得1imt)一0.(28)由")的定义,知1img(n)n一0.(29)由(27),(28)及(29)式可得limEIIW一O.由引理1可得Vn>0,有垒(A:)∑(A~-D.Eilf(Yt)≤Kn一….(3o)由引理1及r.v.f(YD的定义容易看出V",Vk—O,1,…,,V∈力.A:=:IIf(Y(oJ))/A:≤Kak+1一)c--tl~一.因此存在收敛于0的正数序列{b),满足J一"i.1_≤,(31)lV,V"sup(=fill(Y,())}1/AD≤-由于ElIW一0.故对任意固定的t>0,存在()使得V≥"(£),I"(IIWll>}≤P(IIW¨字一EIIW>专).据引理5及(31)式可得P(IIW一号}≤2exp嗑一(t+叁jln(1+))注意到6/△:≥Kn',t--c)~ttmb一0,故当》1时P(IIW>}≤2exp{t一壶1n(1+惫)一矗1n(1+惫))≤2exp{_去1n(1+凳)}≤",●●●●●●J●●●●【11)令第2期刘吉定:经验过程的Cesaro大效定律93从而vt>O,EP{llw.1l>f)<...由Bore1一Cantelli引理可得(25)式.至此完成了定理充分性的证明.必要性由A:=,(4)几乎处处收敛可得蚱:(,(一一.一s?由引理6可得EIIf(x.)一f(X'o).< (32)由(1),(32),Fubini定理及凸函数的性质可得EIIf(X.)<...这就完成了定理必要性的证明.4讨论下面就而ll(A:=1)/If(X.)II随机有界性的验证问题作点说明:当只包含有限个函数时,随机有界条件已经成立,无须假设.事实上,令={f",",…,),对于给定的jE{,2,…,}?令i一玎走(A:=1)".I(),一1,2…,矗一o,1,…,.众所周知;Lz(Ei)一Ⅳ(.,1).由此可见,vE>.,jM>O,使得P{赤II(蚱lIf(XII>)≤砉P{I砉(蚱n>等)<e.i-】 (IIii)即i南lI似:=1)nIf(x?)I'~zII随机有界.因此可知,随机有界这一假设条件是合理的.由上可见,本文中定理是实值Cesaro大数定律在经验过程中的推广.参考文献1LedouxM'parisontheorems,randomgeometryandsomelimittheorems forempiricalprocesses.AnnProbt1989t17(2),596~831rgedeviations,moderatedeviationsandLILforempiricalprocesses.AnnProb+ 1994,22(1):17~273DudleyRM.Centrallimittheoremsforempiricalmeasures.AnnProb,1978+6(5):899~929 4ShaoQM+YuH.Weakconvergenceforweightedempiricalprocessesofdependentsequen ces.AnnProb.1996,24(4)2098~21275HeinkeIB.An533~546lawoflargenumbersinCesaro'sseDse.JTheoretProb,1990,3(4)6ZygmundA.Trigometricalseries.Warsaw;MonografieMatematyczne.1935.427GinEtZinnJ.Lecturesonthecentrallimittheoremforempiricalprocesses.LectureNotesin Math.94武议化工学院第20卷1986,1Z21,50~1138Hoffmann—J~rgensenJ.SumsofindependentBanachspacevaluedrandomvariables.StudiaMath,1974, 52,159~1869deAcostaA.StrongexponentialintegrabilityotsumsofindepedentB—valuedrandomvectors-ProbMathStat,l980,(1):133~15010昊智泉.王向忱.巴氏空间上的概率论.长春:吉林大学出敝社,1990.33111StoutWF.Almostsureconvergence.NewY ork:AcademicPress,1974-15912KuelbsJ,ZinnJ.Somestabilityresultsforvectorvaluedrandomvariables.AnnProb,1979, 7(1):75~84TheCesaro'SLawofLargeNumbersforEmpiricalProcessesLiuJiding(DepartmentofBasicCourses,WuhanlnstituteofChemicalTechnology,Wuhan430073tCh ina)AbstractInthispaper.thesufficientandnecessaryconditionfortheCesaro'slawoflarge numbersinempiricalprocessesareobtained.LetXisarandomelementonabasicprobabili—tyspace(n,,尸),takingvaluesinameasurablespace(,),and{XI)^independent copiesofX.Underdefiniteconditionsonthefamilyot一measurablefunctions,foralln∈(O,1),Itisobtainedthat∑A:=If(X.)11一o,a.s.……ifandonlyifEllf(x)<oo.Keywordsrandomelementinnormedspace;empiricalprocess;sumsofi.i.d.randomele—ments。
littlewood paley 定理 -回复
littlewood paley 定理-回复"Littlewood-Paley Theorem: A Journey through its Understanding and Applications"Introduction:The Littlewood-Paley theorem is a fundamental result in harmonic analysis. It provides a powerful tool for studying the behavior of functions in relation to their frequency content. In this article, we will embark on a journey to understand this theorem, step by step. We will explore its origins, delve into its proof, and discuss its wide-ranging applications.1. Origins of the Littlewood-Paley Theorem:The theorem is named after the prominent mathematicians John Edensor Littlewood and Raymond Paley, who independently formulated its core ideas in the early 1920s. Littlewood's motivation came from his work on trigonometric series, while Paley was studying Fourier series. Their contributions were eventually merged into a unified theorem that revolutionized the field of harmonic analysis.2. Statement of the Littlewood-Paley Theorem:Let's state the central result of the theorem. For any function f in L^p(R^n), where p lies between 1 and infinity, we have the following equivalence in the norm:f _p ~ \{(\lambda, \xi) : \xi \approx 2^{-\lambda}}\hat{f}(\xi) ^p \lambda^{-n/p} _{\ell^2_{\lambda}}^p, where \hat{f}(\xi) denotes the Fourier transform of f.3. Proof Sketch:To prove the theorem, we outline a few key steps. First, we use the decomposition of f into its frequency components by employing dyadic intervals. Then, we introduce theLittlewood-Paley square functions, defined as the sum of the squares of the Fourier transforms of these frequency components, suitably weighted by the dyadic scale and spherical harmonics. Next, we show that the Littlewood-Paley square functions obey certain key properties, such as boundedness on L^p spaces. Finally, we utilize the convolution properties of these square functions to establish the equivalence stated in the theorem.4. Applications of the Littlewood-Paley Theorem:The Littlewood-Paley theorem has found applications in numerous areas of analysis and beyond. Here, we highlight a few notable ones.a. Harmonic Analysis: The theorem is instrumental in studying the behavior of functions in function spaces such as BMO (bounded mean oscillation) and Hardy spaces. It helps establish key properties, such as the boundedness of singular integrals and thecharacterization of weak atomic functions.b. Partial Differential Equations: The theorem provides powerful techniques for analyzing the regularity of solutions to certain types of partial differential equations, particularly those involving elliptic operators. By controlling the frequency content of solutions through Littlewood-Paley theory, one can deduce important regularity results.c. Signal Processing: The Littlewood-Paley theorem has been widely utilized in the field of signal processing. For instance, it forms the basis for the design and analysis of wavelet transforms, which are indispensable in image compression and denoising algorithms.d. Probability Theory: The theorem is also employed in the study of stochastic processes and their properties. It has proven useful in establishing various limit theorems, such as the central limit theorem, and understanding the behavior of random processes in adapted frameworks.Conclusion:In conclusion, the Littlewood-Paley theorem stands as a cornerstone of harmonic analysis, with far-reaching consequences across several areas of mathematics. From its humble beginnings in the early 20th century, it has grown into apowerful tool offering deep insights into the behavior of functions based on their frequency content. We have taken a step-by-step journey through its understanding and explored its many applications. As mathematicians continue to delve into the intricacies of this theorem, its impact is likely to extend even further, enriching our understanding of the world around us.。
gmm
1.2 Single Equation Linear GMM
Consider the linear regression model yt = z0 t δ 0 + εt , t = 1, . . . , n (1.1)
where zt is an L × 1 vector of explanatory variables, δ 0 is a vector of unknown coefficients and εt is a random error term. The model (1.1) allows for the possibility that some or all of the elements of zt may be correlated with the error term εt , i.e., E [ztk εt ] 6= 0 for some k. If E [ztk εi ] 6= 0 then ztk is called an endogenous variable . It is well known that if zt contains endogenous variables then the least squares estimator of δ 0 in (1.1) is biased and inconsistent. Associated with the model (1.1), it is assumed that there exists a K × 1 vector of instrumental variables xt which may contain some or all of the elements of zt . Let wt represent the vector of unique and non-constant elements of {yt , zt , xt }. It is assumed that {wt } is a stationary and ergodic stochastic process. The instrumental variables xt satisfy the set of K orthogonality conditions E [gt (wt , δ 0 )] = E [xt εt ] = E [xt (yt − z0 (1.2) t δ 0 )] = 0 where gt (wt , δ 0 ) = xt εt = xt (yt − z0 t δ 0 ). Expanding (1.2), gives the relation Σxy = Σxz δ 0 where Σxy = E [xt yt ] and Σxz = E [xt z0 t ]. For identification of δ 0 , it is required that the K × L matrix E [xt z0 t ] = Σxz be of full rank L. This rank condition ensures that δ 0 is the unique solution to (1.2). Note, if K = L, then Σxz is invertible and δ 0 may be determined using
怎样让数学学好(Howtolearnmathwell)
怎样让数学学好(How to learn math well)How to learn math well?Mathematics has always been an important tool for human beings to practice, and it is one of the most basic courses in basic education. Each student hopes to master mathematics knowledge, train and improve his calculation ability, logical thinking ability, spatial imagination ability, creative ability, and preliminary application to mathematics. However, for a junior high school student who has just entered junior high school from primary school, how can he learn mathematics well? I think we can start by grasping all kinds of study habits. Entering junior high school from primary school is a major turning point in the learning phase. According to people's physical and psychological development of junior high school students, it is at a critical stage of forming the habit, if not timely to seize this opportunity to form good learning habits, it is easy to catch a lot of bad learning habits, and seriously influence the development of intelligence and ability. Good study habit is an important psychological factor for stimulating thinking, developing ability and developing personality. It is the basis of achieving good teaching effect. So it is the key to learn good habits to cultivate good study habits. The following four aspects of how to develop and shape good learning habits.First, reading habitsThis is the basic skill of self-study ability. According to the scores of famous university study in the United States and the former Soviet Union, those successful scientists have 20%~25% knowledge from school, and the knowledge of 75%~80% is to relyon them after leaving work, through self-study and research to obtain the. According to psychological rules, junior high school students already have the ability to read, but because of the influence of intuitive imitation habits in primary schools, many students mistake mathematics textbooks as exercise sets. Therefore, from the beginning of the first year, we should pay attention to correct their mistakes, study habits, and set up mathematical textbooks, also need to read the correct ideas, and pay attention to how to read mathematics textbooks.1., each class must be prepared to preview the habit, and strive to preview the discovery that they do not understand the problem, in order to be able to listen to the problem. In class, pay attention to how the teacher reads the text, from which he can learn how to analyze and define the key words, words and sentences in the theorem, and the connection with the old knowledge.2., often sum up the knowledge learned, training review habits. At the beginning, can follow the teacher summed up a lesson or a unit, a stage according to the teacher's review outline, with their own problems to delve into the text, the final transition to promote themselves by their own induction, repeated reading, timely review, new.Two, note habitsA good memory is worse than a bad pen". The middle school mathematics classroom is rich in content, capacity is relatively large, to learn mathematics, from junior high school must attach great importance to the cultivation of the habitof taking notes in class, class notes can also constrain energy dispersion, improve the efficiency of class. In general, in addition to record the lecture notes outline, is mainly remembered, the teacher summarized the key ideas, methods and contents of the account. Pay special attention to the notes and questions in the lecture at any time. In the two aspects of "listening" and "recording", listening is the foundation".In order to gradually improve the quality of class notes, students should make appropriate exchanges and learn from each other.Three, hands-on practice, cooperation, exchange habitsTrue knowledge comes from practice". Hands-on practice can concentrate attention, improve interest in learning, and can deepen the impression and understanding of learning objects. In practice, we can link the knowledge of the book with the actual things, and form a correct and profound concept. In practice, the brain and the use of expert activities, and gradually formed and developed their own cognitive structure, can form skills, development ability. In practice, develop a "pre - guess - hands-on experiment - operation results - summary summary" habits."Three men go together, and there must be my teachers."". The results of learning exchanges between the students from each one airs his own views. It can achieve the functions of thinking, moving, opening, starting, stimulating thinking, active atmosphere and arousing enthusiasm.Four, homework habitsMathematics homework is an important link to strengthen mathematical knowledge, stimulate learning interest and train mathematical ability. Some students regard homework as a burden. After class, they only rush to answer questions in class. They often have a single solution. Some of them are sloppy, careless, careless in format and even copied. This misses the opportunity to train, seriously affecting the learning effect. We should correctly understand the purpose of doing homework and train good habit of homework. Good habit of homework should include:1., to develop the habit of reading before work. Before you do your homework, read the text carefully and see the solution, format, steps and methods of the examples. This is the "quicken work".2. to develop their habits. After reading the questions, first find out what kind of questions the topic is, what conditions it has and what characteristics it has.3., to develop the habit of independent work. If there are special circumstances can not be completed on time, you can explain the situation to the teacher: if you encounter problems will not do, you can ask the teacher or classmate, understand, after the completion of the independent. Never copy in order to cope with a task.4., get into the habit of thinking about doing your homework again. Many students do not pay attention to doing homework again, and then thinking, resulting in erroneous practices inthe minds of stereotypes. Some questions wrong, the teacher revised, you are wrong, that is the reason. As you go on, you will make greater mistakes in new knowledge and new assignments. In order to consolidate the results of your work, you must always give feedback to your previous day's homework before you make new assignments. The feedback includes: (1) the types of questions; (2) problem solving ideas and methods; (3) cause errors; error correction; (4) (5) (collection of error problem is their mistake to collect in one place, marked above four items for future review when the error correction).Five, thinking habitsScientific methods of thinking and good habit of thinking are keys to developing intelligence and developing ability. Psychology tells us, the first stage is the students from image thinking to abstract thinking of the important period of change, so at this time must pay attention to good habit of thinking training. According to the characteristics of junior high school mathematics, good habits of thinking include logicality, thoroughness, divergence, convergence and converse.1. logic. This requires students to answer "yes" and must not take it for granted. In the process of reasoning, we can understand the basis of each step, do not understand, do not write, try to understand, and then continue to reasoning calculus.2. thoroughness. This requires the students to consider everything in a comprehensive way. Such as: the known point C in the line AB, line AB=8cm, line BC=3cm, to find the lengthof the line AC. Fully consider the issue will be discussed in the C segment of AB extension line two on segment AB and C: when C on segment AB, AC=AB-BC=8-3=5cm; when the C extension line of the line AB, AC=AB+BC=8+3=11cm. To develop this habit, pay special attention to the situations and causes that the teacher points out in the class as "error prone" or "not complete".3. divergent. This requires students to use many different ways to solve a problem. To cultivate this habit, we should pay special attention to the teacher's thinking method, problem, extension and analysis when we are talking about multiple solutions. In the process of mathematics study, we should try to develop a habit of seeking a problem with multiple solutions and a problem.4. convergence. This is based on divergent thinking, summarized, in order to achieve multiple questions, a solution, draw inferences from others. The two kinds of thinking, divergence and convergence, can be combined with each other.5. reverse. This requires students to reverse the order of certain formulas, laws, and theorems. As calculated:(-0.38) * 4.58-0.62 * 4.58 can be obtained by using the multiplicative distribution law in reverse.Six, questioning habitsConfucius, an ancient great educator in China, always insisted that learning should be understood and that it should be known. Is not only to ask what is "what", but also to ask "why?"".Psychologists tell us,When people accept a new problem, there is a general desire to make a real difference. Students in junior middle school students' active thinking, strong curiosity, psychological requirements should have asked. But due to the old social psychological bondage, not daring to problems "like" and "nonsense", this is the classroom, extracurricular too, make their personality severely stifle, is not conducive to healthy growth. To reverse this situation, requires students to speak boldly and actively discuss and practice in the classroom, after-school qinsi ask, cultivate a good habit to create a love question, students should know the teacher ask the students love Dickens, to develop the knowledge to the bottom of the habit, ready to develop the question the habit of doubt.Developing study habits is a systematic project. It requires the students to have determination, perseverance and patience. "The most valuable knowledge is knowledge about methods," Darwin said". As time passes, the method becomes a natural habit, so the cultivation of good study habits is the key to mastering a treasure trove of knowledge, and the energy released by it is incomparable.。
黑带如何完成一个项目的实例教程
这是黑带如何完成一个项目的实例教程,指导黑带如何更好的完成项目。
如何定义一个项目?项目定义是由冠军来完成的。
我们简单介绍以下项目是如何定义的。
1确定主要商业问题:a目标b目的c可交付使用的2对与生产来说:a循环时间b质量/缺陷水平c耗费3项目的选择a选择项目的工具a1宏观图a2 Pareto图分析a3鱼骨图a4因果矩阵图b项目的标准(评估)b1减少缺陷的70%b2第一年节省$175Kb3项目完成周期为4个月b4最少的资金总额b5黑带的第一个项目必须满足培训目标《6 Sigma项目运作实例》->《定义阶段》->我们在定义阶段做什么--------------------------------------------------------------------------------------------------- 我们在定义阶段需要做什么?1,完成项目陈述。
2,完成项目预测节省金额。
3,完成问题陈述:3.1问题是什么?3.2在哪里和什么时间发现的?3.3问题将涉及哪些工序?3.4谁将受到影响?3.5问题的严重程度是什么?3.6你是如何得知这些的?4,绘制宏观图。
5,描述项目的主线。
6,完成目标陈述。
7,组成项目小组,列出小组成员。
8,完成财务评估。
《6 Sigma项目运作实例》->《定义阶段》->如何进行项目问题陈述--------------------------------------------------------------------------------------------------- 如何进行问题陈述?分六个方面进行问题陈述:1问题是什么?2在哪里和什么时间发现的?3问题将涉及哪些工序?4谁将受到影响?5问题的严重程度是什么?6你是如何得知这些的?《6 Sigma项目运作实例》->《定义阶段》->如何绘制宏观图--------------------------------------------------------------------------------------------------- 如何绘制宏观图?绘制宏观图的顺序:供应商->输入->工序->输出->客户《6 Sigma项目运作实例》->《定义阶段》->项目的目标陈述要点--------------------------------------------------------------------------------------------------- 项目的目标陈述要点:1,目标陈述2,计算方法3,全年节省额确定Team Members成员:1,小组成员要包括技术人员2,包括维修人员(如果需要)3,包括操作者4,小组人员不超过5人(特殊情况除外)。
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The Annals of Probability
2006,Vol.34,No.1,427–428
DOI:10.1214/009117905000000521
c
Institute of Mathematical Statistics ,2006CORRECTION CENTRAL LIMIT THEOREMS FOR ADDITIVE FUNCTIONALS OF THE SIMPLE EXCLUSION PROCESS By S.Sethuraman Iowa State University Definition 2.1in the above paper is incorrectly stated.In the proof of Theorem 2.1,which gives an invariance principle for certain processes sat-isfying Definition 2.1,conditions in Definition 2.1are sufficient to deduce finite-dimensional convergence,but not enough to apply a maximal inequal-ity for “demimartingales”to obtain tightness.The problem is Definition 2.1,as stated,only considers “pair increment associations”and not more general associations needed for the demimartingale property.We slightly strengthen the definition here in this correction so that the proof of tightness in Theo-rem 2.1holds.Details of how this is accomplished are given below.By substituting the corrected Definition 2.1for the previous one,all re-sults in the article hold as written.In particular,Proposition 2.1,which is the link between Theorem 2.1and the main results,and which states certain additive processes satisfy Definition 2.1,holds with the same argument.Corrected Definition 2.1.Let { v (t )=(v 1(t ),...,v m (t )):t ≥0}be an m -dimensional L 2process with stationary increments.We say v has weakly positive associated increments if E [φ( v (t +s )− v (s ))ψ( v (s 1),..., v (s n ))]≥E [φ( v (t ))]E [ψ( v (s 1),..., v (s n ))]for all coordinatewise increasing functions φ:R m
→R and ψ:(R m )n →R ,
and all s,t ≥0,0≤s 1<···<s n =s and n ≥1.We remark the earlier Definition 2.1only stipulated the pair condition
E [φ( v (t +s )− v (s ))ψ( v (s ))]≥E [φ( v (t ))]E [ψ( v (s ))].
2CORRECTION
We now indicate how the modified definition applies in the proof of tight-ness in Theorem2.1.Following standard tightness arguments,one needs to prove for a continuous mean-zero scalar process v(t)with stationary incre-ments satisfying corrected Definition2.1,with v(0)=0,lim t→∞t−1E[v(t)2]=σ2and t−1/2v(t)⇒N(0,σ2)that,for allε>0,
lim δ↓0lim sup
α→∞
1
α =0.
(1)
Forδ>0,let A be a countable dense set of[0,δ],and for n≥1,let A n be a set of n points so that A n↑A.Fix also thatδ∈A andδ∈A1.Then,for α≥1,by continuity sup t∈[0,δ]|v(αt)|=sup t∈A|v(αt)|,and for n large enough
P sup t∈A|v(αt)|>ε√α .
Let now0≤t1<···<t n−1<t n=δbe a labeling of A n.From the cor-rected definition and mean-zero property E[v(t)]=0we have E[(v(αt j+1)−v(αt j))ψ(v(αt j),...,v(αt1))]≥0for all1≤j≤n−1and increasingψ,and so{v(αt):t∈A n}is a demimartingale(cf.[1],page362).Hence,we can apply the maximal inequality([2],Corollary6)and variance convergence limα→∞(αδ)−1E[v(αδ)2]=σ2to get
lim sup
α→∞
P sup t∈A n|v(αt)|>ε√δ2√
α]=(2πσ2)−1/2 ∞(ε/2)δ−1/2exp(−x2/(2σ2))dx,and so(1)holds. Also,we note typos:in line8,page281,change2/(πdet(σ2p))to1/(π×(det(σ2p))1/2);in lines9–10,page286,ds to dr;in line10,page293,=to ≥;in line29,page294,change>0to<∞;in line27,page297,exp(λ2s−λ−1)(−λs)should be(λ2s−2λ)exp(−λs).
REFERENCES
[1]Newman,C.M.and Wright,A.L.(1982).Associated random variables and mar-
tingale inequalities.Z.Wahrsch.Verw.Gebiete59361–371.MR0721632
[2]Sethuraman,S.(2000).Central limit theorems for additive functionals of the simple
exclusion process.Ann.Probab.28277–302.MR1756006
Department of Mathematics
Iowa State University
396Carver Hall
Ames,Iowa50011
USA
e-mail:sethuram@。