sfabz {FABInference}

Bayes-optimal spending function

Description

Compute Bayes optimal spending function

Usage

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

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.

Value

a scalar value giving the optimal tail-area probability

Author(s)

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")