Compute Bayes optimal spending function

sfabz(theta, psi, alpha = 0.05)

Arguments

theta

value of theta being tested

psi

a list of parameters for the spending function, including

  1. mu, the prior expectation of E[y]

  2. tau2, the prior variance of E[y]

  3. sigma2 the variance of y

alpha

level of test

Value

a scalar value giving the optimal tail-area probability

Details

This function computes the value of s that minimizes the acceptance probability of a biased level-alpha test for a normal population with known variance, under a specified prior predictive distribution.

Author

Peter Hoff

Examples

thetas<-seq(-1,1,length=100) s<-NULL for(theta in thetas){ s<-c(s,sfabz(theta,list(mu=0,tau2=1,sigma2=1)) ) } plot(thetas,s,type="l")