matlab中二元正态分布函数.doc

matlab中二元正态分布函数 function data1, data2 = twogaussian(n1,mu1,cov1,n2,mu2,cov2);% data1, data2 = twogaussian(n1,mu1,sigma1,n2,mu2,sigma2);% Function to simulate data from 2 Gaussian densities in d dimensions% and to plot the data in the first 2 dimensions% INPUTS:% n1, n2: two integers, size of data set 1 and 2 respectively% mu1, mu2: two vectors of dimension 1 x d, means% for data set 1 and 2% cov1, cov2: two matrices of dimension d x d, covariance% matrices for data set 1 and 2 respectively% OUTPUTS:% data1: n1 x d matrix of data for data set 1% data2: n2 x d matrix of data for data set 2% check that the dimensionality of the mus and sigmas are consistentd1 = length(mu1); d2 = length(mu2); if (d1=d2) error(means are of different lengths); end;d = length(mu1); % d is the dimensionality of the datad1 d2 = size(cov1); if (d1=d2) error(cov1 is a non-square covariance matrix); end; if (d1=d) error(cov1 is of different dimensionality to mu1); end; d1 d2 = size(cov2); if (d1=d2) error(cov2 is a non-square covariance matrix); end; if (d1=d) error(cov2 is of different dimensionality to mu2); end;% Call the function mvnrnd.m to generate the two data setsdata1 = mvnrnd(mu1,cov1,n1);data2 = mvnrnd(mu2,cov2,n2); % Now plot the two data sets as a two-dimensional scatter plot% if d = 2: plot dimension1 on the xaxis and dimension 2 on the% yaxis. Plot the points from data1 as green circles o, and the% points from data2 as red crosses x.if . figure % open a figure window plot(data1(:,1),data1(:,2),b.);. % now plot data1 axis(-6 6 -6 6); % fix the lengths of the axes hold % hold the figure to overlay a 2nd plot plot(data2(:,1),data2(:,2),rx);% now plot data 2 xlabel(Dimension 1); ylabel(Dimension 2); title(Simulation of two-class Gaussian data in two dimensions);endfunction r = mvnrnd(mu,sigma,cases);%MVNRND Random matrices from the multivariate normal distribution.% R = MVNRND(MU,SIGMA,CASES) returns a matrix of random numbers% chosen from the multivariate normal distribution with mean vector,% MU, and covariance matrix, SIGMA. CASES is the number of rows in R.% SIGMA is a square positive definite matrix with size equal to% the length of MU% Adapted from Mathworks functionm1 n1 = size(mu);c = max(m1 n1);if m1 .* n1 = c error(Mu must be a vector.);endm n = size(sigma);if m = n error(Sigma must be square);endif m = c error(The length of mu must equal the number of rows in sigma.);endT p = chol(sigma);if p = 0