mochoice {mcsm} | R Documentation |
Using a Gibbs sampling strategy of changing one indicator at a time, this function explores the space of models and returns the most likely models among those visited. The data used in this example is swiss, with four explanatory variables.
mochoice(Niter = 10^4)
Niter |
Number of MCMC iterations |
model |
Sequence of model indicators visited by the MCMC algorithm |
top |
Five most likely models |
For more details, see Chapter 3 of Bayesian Core (2007, Springer-Verlag) by J.-M. Marin and C.P. Robert, since the procedure is derived from the developments in this chapter.
Christian P. Robert and George Casella
From Chapter 6 of EnteR Monte Carlo Statistical Methods
mochoice(10^3)