常用matlab函数的参数估计

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[unifit ]函数----均匀分布的参数估计

[aht bat ]=unifit(x)

[ahat bhat,ACI,BCI ]=unifit(x)

[aht bat,ACI,BCI ]=unifit(x,ALPHA)

[normfit]函数正态分布的参数估计

[muhat,sigmahat] = normfit(data)[muhat,sigmahat,muci,sigmaci] = normfit(data)[muhat,sigmahat,muci,sigmaci] = normfit(data,alpha)[...] = normfit(data,alpha,censoring)[...] = normfit(data,alpha,censoring,freq)[...] = normfit(data,alpha,censoring,freq,options)

Muhat(u的估计值)

sigmahat(q的估计值)

muci,sigmaci(区间)

data = normrnd(10,2,100,2);

[mu,sigma,muci,sigmaci] = normfit(data)

mu =

10.1455 10.0527

sigma =

1.9072

2.1256

muci =

9.7652 9.6288

10.5258 10.4766

sigmaci =

1.6745 1.8663

2.2155 2.4693

二项分布的参数估计

【binofit】函数

phat = binofit(x,n)

[phat,pci] = binofit(x,n)

[phat,pci] = binofit(x,n,alpha)

r = binornd(100,0.6)

[phat,pci] = binofit(r,100)

r =

phat =

0.5500

pci =

0.4473 0.6497

[betafit]函数–计算beta分布的参数估计phat = betafit(data)

[phat,pci] = betafit(data,alpha)Description

data = betarnd(4,3,100,1);

[p,ci] = betafit(data,0.01)

p =

3.9081 3.0022

ci =

2.4864 1.8530

5.3299 4.1513

[expfit]函数—指数分布的参数估计

parmhat = expfit(data)

[parmhat,parmci] = expfit(data)

[parmhat,parmci] = expfit(data,alpha)

[...] = expfit(data,alpha,censoring)

[...] = expfit(data,alpha,censoring,freq)

data = exprnd(3, 100, 1);

[parmhat, parmci] = expfit(data, 0.01) parmhat =

3.0398

parmci =

2.3817

3.9934

【poissfit】函数---泊松分布

lambdshat = poissfit(data)

[lambdahat,lambdaci] = poissfit(data)

[lambdahat,lambdaci] = poissfit(data,alpha)

r = poissrnd(5,10,2);

[l,lci] = poissfit(r)