logctablepost {LearnBayes} | R Documentation |
Computes the log posterior density for the difference and sum of logits in a 2x2 contingency table for independent binomial samples and uniform prior placed on the logits
logctablepost(theta,data)
theta |
matrix of parameter values where each row represents (difference of logits, sum of logits) |
data |
vector containing number of successes and failures for first sample, and then second sample |
vector of values of the log posterior where each value corresponds to each row of the parameters in theta
Jim Albert
s1=6; f1=2; s2=3; f2=10 data=c(s1,f1,s2,f2) theta1=c(2,4); theta2=c(1,1) theta=rbind(theta1,theta2) logctablepost(theta,data)