How to compute a P-value for a complex mixture of chi-squared distributions in R
On Jun 1, 2013, at 06:32 , Tiago V. Pereira wrote:
Hello, R users! I am struggling with the following problem: I need to compute a P-value for a mixture of two chi-squared distributions. My P-value is given by: P = 0.5*prob(sqrt(chi2(1)) <= x) + 0.5*prob(sqrt(chi2(2)) <= x) In words, I need to compute the p-value for 50?50 mixture of the square root of a chi-squared random variable with 1 degree of freedom and the square root of a chi-squared with two degrees of freedom. Although I can quickly simulate data, the P-values I am looking for are at the tail of the distribution, that is, alpha levels below 10^-7. Hence, simulation is not efficient. Are you aware of smart approach?
Er,... Anything wrong with 0.5 * pchisq(x^2, 1) + 0.5 * pchisq(x^2, 2) ??? -pd
All the best, Tiago
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