chi2pdf - n independent standard normal observations, then...

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chi2pdf Chi-square probability density function Syntax Y = chi2pdf(X,V) Description Y = chi2pdf(X,V) computes the chi-square pdf at each of the values in X using the corresponding degrees of freedom in V . X and V can be vectors, matrices, or multidimensional arrays that have the same size, which is also the size of the output Y . A scalar input is expanded to a constant array with the same dimensions as the other input. The degrees of freedom parameters in V must be positive integers, and the values in X must lie on the interval [0 Inf] . The chi-square pdf for a given value x and degrees of freedom is where ( · ) is the Gamma function. If x is standard normal, then x 2 is distributed chi-square with one degree of freedom. If x 1 , x 2 , . .., x n are
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Unformatted text preview: n independent standard normal observations, then the sum of the squares of the x 's is distributed chi-square with n degrees of freedom (and is equivalent to the gamma density function with parameters /2 and 2). Examples nu = 1:6; x = nu; y = chi2pdf(x,nu) y = 0.2420 0.1839 0.1542 0.1353 0.1220 0.1120 The mean of the chi-square distribution is the value of the degrees of freedom parameter, nu . The above example shows that the probability density of the mean falls as nu increases. See Also chi2cdf | chi2inv | chi2rnd | chi2stat | pdf How To Chi-Square Distribution Provide feedback about this page chi2inv chi2rnd 1984-2009 The MathWorks, Inc. Terms of Use Patents Trademarks Acknowledgments...
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This note was uploaded on 11/29/2010 for the course ECE 302 taught by Professor Gelfand during the Spring '08 term at Purdue University-West Lafayette.

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chi2pdf - n independent standard normal observations, then...

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