simmvp {bayesm} | R Documentation

## Simulate from Multivariate Probit Model

### Description

`simmvp` simulates from the multivariate probit model.

### Usage

    simmvp(X, p, n, beta, sigma)

### Arguments

`X` | n*p x length(beta) Design matrix
`p` | dimension of the MVP
`n` | number of observations
`beta` | coefficient vector
`sigma` | p x p covariance matrix

### Value

a list of

`y` | p*n vector of 0/1 binary outcomes
`X` | Design matrix
`beta` | coefficients
`sigma` | covariance matrix

### Warning

This routine is a utility routine that does not check the input arguments for proper dimensions and type.

### Author(s)

Peter Rossi, Graduate School of Business, University of Chicago, Peter.Rossi@ChicagoGsb.edu.

### References

For further discussion, see Bayesian Statistics and Marketing by Rossi, Allenby and McCulloch, Chapter 4.
http://gsbwww.uchicago.edu/fac/peter.rossi/research/bsm.html

### See Also

`rmvpGibbs`

[Package bayesm version 2.0-8 Index]