R: Create an object of class BayesFactor from MCMCpack output

BayesFactor {MCMCpack} | R Documentation

## Create an object of class BayesFactor from MCMCpack output

### Description

This function creates an object of class `BayesFactor` from MCMCpack output.

### Usage

    BayesFactor(...)

    is.BayesFactor(BF)

### Arguments

`...` | MCMCpack output objects. These have to be of class `mcmc` and have a `logmarglike` attribute. In what follows, we let `M` denote the total number of models to be compared.
`BF` | An object to be checked for membership in class `BayesFactor`.

### Value

An object of class `BayesFactor`. A `BayesFactor` object has four attributes. They are: `BF.mat` an M \times M matrix in which element i,j contains the Bayes factor for model i relative to model j; `BF.log.mat` an M \times M matrix in which element i,j contains the natural log of the Bayes factor for model i relative to model j; `BF.logmarglike` an M vector containing the log marginal likelihoods for models 1 through M; and `BF.call` an M element list containing the calls used to fit models 1 through M.

### See Also

`MCMCregress`

### Examples

    ## Not run:
    data(birthwt)

    model1 <- MCMCregress(bwt~age+lwt+as.factor(race) + smoke + ht,
                         data=birthwt, b0=c(2700, 0, 0, -500, -500,
                                            -500, -500),
                         B0=c(1e-6, .01, .01, 1.6e-5, 1.6e-5, 1.6e-5,
                              1.6e-5), c0=10, d0=4500000,
                         marginal.likelihood="Chib95", mcmc=10000)

    model2 <- MCMCregress(bwt~age+lwt+as.factor(race) + smoke,
                         data=birthwt, b0=c(2700, 0, 0, -500, -500,
                                            -500),
                         B0=c(1e-6, .01, .01, 1.6e-5, 1.6e-5, 1.6e-5),
                         c0=10, d0=4500000,
                         marginal.likelihood="Chib95", mcmc=10000)

    model3 <- MCMCregress(bwt~as.factor(race) + smoke + ht,
                         data=birthwt, b0=c(2700, -500, -500,
                                            -500, -500),
                         B0=c(1e-6, 1.6e-5, 1.6e-5, 1.6e-5,
                              1.6e-5), c0=10, d0=4500000,
                         marginal.likelihood="Chib95", mcmc=10000)

    BF <- BayesFactor(model1, model2, model3)
    print(BF)

    ## End(Not run)

[Package MCMCpack version 1.4-0 Index]