bprobit.probs: Simulates fitted probabilities for a probit regression model

In LearnBayes: Functions for Learning Bayesian Inference

Description

Gives a simulated sample for fitted probabilities for a binary response regression model with a probit link and noninformative prior.

Usage

bprobit.probs(X1,fit)

Arguments

X1	matrix where each row corresponds to a covariate set
fit	simulated matrix of draws of the regression vector

Value

matrix of simulated draws of the fitted probabilities, where a column corresponds to a particular covariate set

Author(s)

Jim Albert

Examples

response=c(0,1,0,0,0,1,1,1,1,1)
covariate=c(1,2,3,4,5,6,7,8,9,10)
X=cbind(1,covariate)
m=1000
fit=bayes.probit(response,X,m)
x1=c(1,3)
x2=c(1,8)
X1=rbind(x1,x2)
fittedprobs=bprobit.probs(X1,fit$beta)

LearnBayes documentation built on May 1, 2019, 7:03 p.m.