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Date: 7-2-2021
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Date: 21-3-2021
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If have normal independent distributions with mean 0 and variance 1, then
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(1) |
is distributed as with
degrees of freedom. This makes a
distribution a gamma distribution with
and
, where
is the number of degrees of freedom.
More generally, if are independently distributed according to a
distribution with
,
, ...,
degrees of freedom, then
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(2) |
is distributed according to with
degrees of freedom.
The probability density function for the distribution with
degrees of freedom is given by
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(3) |
for , where
is a gamma function. The cumulative distribution function is then
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(4) |
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(5) |
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(6) |
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(7) |
where is an incomplete gamma function and
is a regularized gamma function.
The chi-squared distribution is implemented in the Wolfram Language as ChiSquareDistribution[n].
For ,
is monotonic decreasing, but for
, it has a maximum at
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(8) |
where
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(9) |
The th raw moment for a distribution with
degrees of freedom is
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(10) |
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(11) |
giving the first few as
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(12) |
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(13) |
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(14) |
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(15) |
The th central moment is given by
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(16) |
where is a confluent hypergeometric function of the second kind, giving the first few as
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(17) |
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(18) |
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(19) |
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(20) |
The cumulants can be found via the characteristic function
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(21) |
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(22) |
Taking the natural logarithm of both sides gives
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(23) |
But this is simply a Mercator series
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(24) |
with , so from the definition of cumulants, it follows that
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(25) |
giving the result
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(26) |
The first few are therefore
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(27) |
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(28) |
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(29) |
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(30) |
The moment-generating function of the distribution is
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(31) |
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(32) |
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(33) |
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(34) |
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(35) |
so
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(36) |
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(37) |
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(38) |
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(39) |
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(40) |
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(41) |
If the mean is not equal to zero, a more general distribution known as the noncentral chi-squared distribution results. In particular, if are independent variates with a normal distribution having means
and variances
for
, ...,
, then
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(42) |
obeys a gamma distribution with , i.e.,
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(43) |
where .
REFERENCES:
Abramowitz, M. and Stegun, I. A. (Eds.). Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables, 9th printing. New York: Dover, pp. 940-943, 1972.
Beyer, W. H. CRC Standard Mathematical Tables, 28th ed. Boca Raton, FL: CRC Press, p. 535, 1987.
Kenney, J. F. and Keeping, E. S. "The Chi-Square Distribution." §5.3 in Mathematics of Statistics, Pt. 2, 2nd ed. Princeton, NJ: Van Nostrand, pp. 98-100, 1951.
Press, W. H.; Flannery, B. P.; Teukolsky, S. A.; and Vetterling, W. T. "Incomplete Gamma Function, Error Function, Chi-Square Probability Function, Cumulative Poisson Function." §6.2 in Numerical Recipes in FORTRAN: The Art of Scientific Computing, 2nd ed. Cambridge, England: Cambridge University Press, pp. 209-214, 1992.
Spiegel, M. R. Theory and Problems of Probability and Statistics. New York: McGraw-Hill, pp. 115-116, 1992.
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