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Chi-square distribution with k degrees of freedom is a distribution of the sum of squares of k random variables having normal distribution with mean equal to 0 and standard deviation equal to 1.
Probability density function for chi-square distribution is:
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Cumulative distribution function of the the chi-square distribution is:
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ChiSquareDistribution and ChiSquareCDistribution subroutines are used to calculate the areas under the left and right tails of the graph (i.e. to calculate cumulative distribution function and its own complement). InvChiSquareCDistribution subroutine calculates the inverse cumulative distribution function. Subroutines use the above mentioned formula which calculates cumulative distribution function by using an incomplete gamma-function.
This article is intended for personal use only.
C# source.
C++ source.
C++ source. MPFR/GMP is used.
GMP source is available from gmplib.org. MPFR source is available from www.mpfr.org.
FreePascal version.
Delphi version.
VB.NET version.
VBA version.
Python version (CPython and IronPython are supported).
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ALGLIB® - numerical analysis library, 1999-2012. |