www.gusucode.com > classification_matlab_toolbox分类方法工具箱源码程序 > code/Classification_toolbox/Other/mean_bootstrap.m
function [mu, bias, varjack] = mean_bootstrap(data, B) %Find the estimate of the mean, it's bias and variance using the bootstrap estimator method %Inputs: % data - The data from which to estimate % B - Number of sets to draw %Outputs: % mu - The mean % bias - The bias of the estimator % var - The variance of the estimate [D, N] = size(data); mu_star = zeros(D,B); for i = 1:B, %Draw N samples from the data, with replacement indices = zeros(1,N); for j = 1:N, indices(j) = 1 + floor(rand(1)*N); end %Average the data points chosen mu_star(:,i) = mean(data(:,indices)')'; end mu = 1/B*sum(mu_star')'; bias = mu-mean(data')'; varjack = 1/B*sum((mu_star-mu*ones(1,B))'.^2)';