E(X^r) = gamma(alpha+r)/gamma(alpha) = alpha*(alpha+1)*...*(alpha+r-1).
Therefore, the r-th moment of the product of two chi-squares with the same number of degrees of freedom is just the square of this expression. This same approach can be used to obtain moments of all orders for products of an arbitrary number of chi-squares with different numbers of degrees of freedom.
Somewhat more generally, if the two chi-squares arose in the same linear model context, if they are NOT independent, then I might expect them to be something like (X1+X2) and (X2+X3), where X1, X2, and X3 are independent. In that case, the above rule could still be used to easily get the expected value and variance, plus (with more effort) moments of higher order.
Beyond that, I know of no general result about products of chi-squares (even when they are independent). I just did a search on "querry.statindex.org" for "product of chi-square" and got nothing. When I searched for "product of gamma", I got the following:
O'Brien, Robert and Sinha, Bimal K. (1993) On shortest confidence intervals for product of gamma means Calcutta Statistical Association Bulletin, 43, 181-190
Rukhin, Andrew L. and Sinha, Bimal K. (1991)
Decision-theoretic estimation of the product of gamma scales and generalized variance
Calcutta Statistical Association Bulletin, 40, 257-265
Keywords: Admissibility
I don't know if these articles would help you, but they might.
spencer graves
Giovanni Petris wrote:
There is not enough information here: you need to know the joint distribution of the two. If they are independent, the expectation of the product is just the product of expectations - as any elementary textbook will tell you.
Giovanni
Date: Thu, 01 Jul 2004 14:51:31 -0400 From: "Eugene Salinas (R)" <[EMAIL PROTECTED]> Sender: [EMAIL PROTECTED] Precedence: list User-Agent: Mozilla/5.0 (Windows; U; Windows NT 5.1; en-US; rv:1.6b) Gecko/20031205 Thunderbird/0.4
Hi,
Does anyone know what the expectation of the product of two chi-squares distributions is? Is the product of two chi-squared distributions anything useful (as in a nice distribution)?
thanks, eugene.
______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
