Chi-squared CDF
p = distfun_chi2cdf(x,k) p = distfun_chi2cdf(x,k,lowertail)
a matrix of doubles, the outcome, greater or equal to zero
a matrix of doubles, the number of degrees of freedom, k>0 (can be non integer)
a 1-by-1 matrix of booleans, the tail (default lowertail=%t). If lowertail is true (the default), then considers P(X<=x) otherwise P(X>x).
a matrix of doubles, the probability.
Computes the cumulative distribution function of the Chi-squared distribution function.
Any scalar input argument is expanded to a matrix of doubles of the same size as the other input arguments.
// Test with x scalar, k scalar computed = distfun_chi2cdf(4,5) expected = 0.4505840 // Test with expanded x, k scalar computed = distfun_chi2cdf([2 6],5) expected = [0.1508550 0.6937811] // Test with x scalar, k expanded computed = distfun_chi2cdf(4,[4 7]) expected = [0.5939942 0.2202226] // Test with both x,k expanded computed = distfun_chi2cdf([2 6],[3 4]) expected = [0.4275933 0.8008517] // Plot the function h=scf(); k = [2 3 4 6 9 12]; cols = [1 2 3 4 5 6]; lgd = []; for i = 1:size(k,'c') x = linspace(0,10,1000); y = distfun_chi2cdf ( x , k(i) ); plot(x,y) str = msprintf("k=%s",string(k(i))); lgd($+1) = str; end for i = 1:size(k,'c') hcc = h.children.children; hcc.children(size(k,'c') - i + 1).foreground = cols(i); end xtitle("Chi-squared CDF","x","$P(X\leq x)$"); legend(lgd); | ![]() | ![]() |
http://en.wikipedia.org/wiki/Chi-squared_distribution