Description Usage Arguments Value Author(s) References Examples

Based on Booth and Hobert (*JRSS B*, 1999), this function evaluates the maximum
likelihood estimate of a simulated probit model with random effects. The
random effects are simulated by a MCMC algorithm.

1 | ```
randogit(Tem = 10^3, Tmc = 10^2)
``` |

`Tem` |
starting number of MCEM iterations |

`Tmc` |
number of Monte Carlo points in the likelihood approximations |

The function returns two plots, one of *(beta,sigma)* and one
of the true likelihood *L(beta,sigma,u0)*, where *u0*
is the true vector of random effects.

Christian P. Robert and George Casella

From Chapter 2 of **EnteR Monte Carlo Statistical Methods**

1 2 | ```
## Not run: randogit(20,10)
#very small values to let the example run
``` |

mcsm documentation built on May 30, 2017, 1:33 a.m.

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