Description Usage Arguments Value Examples

This function contains the R code for the implementation of Zellner's *G*-prior analysis of
the regression model as described in Chapter 3. The purpose of `BayesRef`

is dual: first, this R function shows how easily automated
this approach can be. Second, it also illustrates how it is possible to get exactly the same
type of output as the standard R function `summary(lm(y~X))`

. In particular,
it calculates the Bayes factors for variable selection, more precisely single variable exclusion.

1 |

`y` |
response variable |

`X` |
matrix of regressors |

`g` |
constant g for the |

`betatilde` |
prior mean on |

`prt` |
boolean variable for printing out the standard output |

`postmeancoeff ` |
posterior mean of the regression coefficients |

`postsqrtcoeff ` |
posterior standard deviation of the regression coefficients |

`log10bf ` |
log-Bayes factors against the full model |

`postmeansigma2` |
posterior mean of the variance of the model |

`postvarsigma2` |
posterior variance of the variance of the model |

1 2 |

```
Loading required package: MASS
Loading required package: mnormt
Loading required package: gplots
Attaching package: 'gplots'
The following object is masked from 'package:stats':
lowess
Loading required package: combinat
Attaching package: 'combinat'
The following object is masked from 'package:utils':
combn
PostMean PostStError Log10bf EvidAgaH0
Intercept 3.4878 0.0304
x1 1.0225 0.0303 Inf (****)
Posterior Mean of Sigma2: 0.2513
Posterior StError of Sigma2: 0.3561
$postmeancoeff
[1] 3.487783 1.022509
$postsqrtcoeff
[1] 0.03039825 0.03034252
$log10bf
[,1]
[1,] Inf
$postmeansigma2
[1] 0.2513425
$postvarsigma2
[1] 0.1268176
```

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