Background information:
I have two samples, X1 and X2. X1 and X2 are categorical (2 or 3 cases). I want to use chi-square test to test whether X1 and X2 are drawn from  the same underlying distribution.  

Question:
Does matlab have a function for chi-square test for two samples, like kstest2?
There is a function called "CHI2GOF", but I haven't figured out how to use it to the 2 sample case.

Any suggestions?

"Arthur Zheng" <hzheng7@gatech.edu> wrote in message <i5m7ns$cuo$1@fred.mathworks.com>...
> Background information:
> I have two samples, X1 and X2. X1 and X2 are categorical (2 or 3 cases). I want to use chi-square test to test whether X1 and X2 are drawn from  the same underlying distribution.  
> 
> Question:
> Does matlab have a function for chi-square test for two samples, like kstest2?
> There is a function called "CHI2GOF", but I haven't figured out how to use it to the 2 sample case.

I am not an expert but what about these?
nsaribradley	Ansari-Bradley test
barttest	Bartlett's test
canoncorr	Canonical correlation
chi2gof	Chi-square goodness-of-fit test
dwtest	Durbin-Watson test
friedman	Friedman's test
jbtest	Jarque-Bera test
kruskalwallis	Kruskal-Wallis test
kstest	One-sample Kolmogorov-Smirnov test
kstest2	Two-sample Kolmogorov-Smirnov test
lillietest	Lilliefors test
linhyptest	Linear hypothesis test
ranksum	Wilcoxon rank sum test
runstest	Runs test for randomness
sampsizepwr	Sample size and power of test
signrank	Wilcoxon signed rank test
signtest	Sign test
ttest	One-sample t-test
ttest2	Two-sample t-test
vartest	Chi-square variance test
vartest2	Two-sample F-test for equal variances
vartestn	Bartlett multiple-sample test for equal variances
zscore	Standardized z-scores
ztest	z-test

Most of them are for continuous distributions. For 2 samples from discrete distributions, chi-square should be the most popular.
That's why I'm wondering whether matlab has such a 2 sample chi square function.

 
"Joel" <esposito@usna.edu> wrote in message <i5n262$70u$1@fred.mathworks.com>...
> I am not an expert but what about these?
> nsaribradley	Ansari-Bradley test
> barttest	Bartlett's test
> canoncorr	Canonical correlation
> chi2gof	Chi-square goodness-of-fit test
> dwtest	Durbin-Watson test
> friedman	Friedman's test
> jbtest	Jarque-Bera test
> kruskalwallis	Kruskal-Wallis test
> kstest	One-sample Kolmogorov-Smirnov test
> kstest2	Two-sample Kolmogorov-Smirnov test
> lillietest	Lilliefors test
> linhyptest	Linear hypothesis test
> ranksum	Wilcoxon rank sum test
> runstest	Runs test for randomness
> sampsizepwr	Sample size and power of test
> signrank	Wilcoxon signed rank test
> signtest	Sign test
> ttest	One-sample t-test
> ttest2	Two-sample t-test
> vartest	Chi-square variance test
> vartest2	Two-sample F-test for equal variances
> vartestn	Bartlett multiple-sample test for equal variances
> zscore	Standardized z-scores
> ztest	z-test

On 9/1/2010 2:58 PM, Arthur Zheng wrote:
> Background information:
> I have two samples, X1 and X2. X1 and X2 are categorical (2 or 3 cases).
> I want to use chi-square test to test whether X1 and X2 are drawn from
> the same underlying distribution.
> Question:
> Does matlab have a function for chi-square test for two samples, like
> kstest2?
> There is a function called "CHI2GOF", but I haven't figured out how to
> use it to the 2 sample case.

You can use CHI2GOF, but it's really intended more for testing goodness 
of fit of a single sample against a distribution family.  You're doing 
something more like contingency table analysis, which is what CROSSTAB 
is for.  Not sure what form your data are in, but any of these should work:

% cook up some sample data
k = 5;
p = rand(1,k); p = p./sum(p);
M = 200; N = 250;
x = randsample(1:k,M,true,p); m = histc(x,1:k);
y = randsample(1:k,N,true,p); n = histc(y,1:k);

% Do the test by hand
phat = (m+n) ./ (M+N);
em = phat*M; en = phat*N;
chi2 = sum(([m n] - [em en]).^2 ./ [em en]);
df = k-1;
pval = 1 - chi2cdf(chi2,df);

% Trick CHI2GOF into doing a two sample test.  Note the
% nparams value must be such that 2*k - nparams - 1 = k-1
[~,pval,stats] = chi2gof(1:10,'ctrs',1:10,'freq',[m n], ...
           'expected',[em en],'nparams',k, 'emin',0)

% Use CROSSTAB
[tbl,chi2,pval] = crosstab([x y],[ones(size(x)) 2*ones(size(y))])

Hope this helps.