Compute Bayes optimal spending function

sfabz(theta, psi, alpha = 0.05)

## Arguments

theta value of theta being tested a list of parameters for the spending function, including mu, the prior expectation of E[y] tau2, the prior variance of E[y] sigma2 the variance of y 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.

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")