The centrality quotient communicates the tendency for a
test to favour evidence shared among all tests over strong
evidence in a single test.
To test the null hypotheses that all p-values are uniform
against a restricted beta family 0 < a <= 1 <= b, the most
powerful pooled p-value linearly combines upper and lower tail
probabilities of the chi-squared distribution with two degrees
of freedom with weights w and (1 - w) where w = (1 - a)/(b - a).
This function uses the individual estimation functions for
central and marginal rejection levels to compute the centrality
quotient for the UMP pooled p-value.