R: Simulates fitted probabilities for a probit regression model

bprobit.probs {LearnBayes} | R Documentation

## Simulates fitted probabilities for a probit regression model

### 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)

[Package LearnBayes version 2.15 Index]