matlab源代码实例

1.硬币模拟试验

源代码：

clear;

clc;

head_count=0;

p1_hist= [0];

p2_hist= [0];

n = 1000;

p1 = 0.3;

p2=0.03;

head = figure(1);

rand('seed',sum(100*clock));

for i = 1:n

tmp = rand(1);

if(tmp <= p1)

head_count = head_count + 1;

end

p1_hist (i) = head_count /i;

end

figure(head);

subplot(2,1,1);

plot(p1_hist);

grid on;

hold on;

xlabel('重复试验次数');

ylabel('正面向上的比率');

title('p=0.3试验次数N与正面向上比率的函数图');

head_count=0;

for i = 1:n

tmp = rand(1);

if(tmp <= p2)

head_count = head_count + 1;

end

p2_hist (i) = head_count /i;

end

figure(head);

subplot(2,1,2);

plot(p2_hist);

grid on;

hold on;

xlabel('重复试验次数');

ylabel('正面向上的比率');

title('p=0.03试验次数N与正面向上比率的函数图');

实验结果：

2.不同次数的随机试验均值方差比较

源代码：

clear ;

clc;

close;

rand('seed',sum(100*clock));

Titles = ['n=5时'

'n=20时'

'n=25时'

'n=50时'

'n=100时'];

Titlestr = cellstr(Titles);

X_n_bar=[0]; %the samples of the X_n_bar

X_n=[0]; %the samples of X_n

N=[5,10,25,50,100];

j=1;

num_X_n = 100;

num_X_n_bar = 100;

h_X_n_bar = figure(1);

for n = 1: num_X_n

for i= 1 : num_X_n_bar

X_n = rand(1,n);

X_n_bar(i) = mean(X_n); %X_n 是我们模拟的对象end

mean_X_n_bar(n) = mean(X_n_bar); %均值

var_X_n_bar(n) = var(X_n_bar);%方差

if(n==5||n==10||n==25||n==50||n==100)

figure(h_X_n_bar)

subplot(2,2,j);

plot(X_n_bar);

grid on;

hold on;

xlabel('重复试验次数');

ylabel('Xn_bar');

axis([0 100 0 1]);

title(Titlestr(j));

j=j+1;

end

end

theory_mean_X_n_bar = [num_X_n];

theory_var_X_n_bar = [num_X_n];

for n=1:100

theory_mean_X_n_bar(n) = 0.5;

theory_var_X_n_bar(n) = 1/(12*n);

end

figure;

subplot(2,1,1);

plot(theory_mean_X_n_bar, '-r');

grid on;

hold on;

plot(mean_X_n_bar,'bo-');

xlabel('n');

ylabel('样本均值的均值');

legend('theory value','sampled value');

subplot(2,1,2);

plot(theory_var_X_n_bar, '-r');

grid on;

hold on;

plot(var_X_n_bar,'bo-');

xlabel('n');

ylabel('样本均值的方差');

legend('theory value','sampled value');实验结果：