mprior-class {BMS} | R Documentation |

## Class "mprior"

### Description

An object pertaining to a BMA model prior

### Objects from the Class

An `mprior`

object holds descriptions and subfunctions pertaining to model priors. The BMA functions `bms`

and post-processing functions rely on this class.

There are currently five model prior structures built into the BMS package, generated by the following functions (cf. the appendix of `vignette(BMS)`

):

`mprior.uniform.init`

: creates a uniform model prior object.

`mprior.fixedt.init`

: creates the popular binomial model prior object with common inclusion probabilities.

`mprior.randomt.init`

: creates a beta-binomial model prior object.

`mprior.pip.init`

: creates a binomial model prior object that allows for defining individual prior inclusion probabilities.

`mprior.customk.init`

: creates a model prior object that allows for defining a custom prior for each model paramter size.

The following describes the necessary slots:

### Slots

`mp.mode`

:A string with a human-readable identifier of the prior.

`mp.msize`

:A scalar holding the prior model size

`mp.Kdist`

:A vector holding the prior probabilities for each parameter size, from `0`

to `K`

. (Not necessary for `bms`

, but for some post-processing functions.

`pmp(ki, molddraw, ...):`

A sub-function returning log-prior model probability depending on `molddraw`

(a logical/numeric indicating the positions of regressors included in the model) and model size `k`

(equivalent to `sum(molddraw)`

.

### Methods

As for now, there are no methods defined with class "mprior" in the signature.

### Author(s)

Martin Feldkircher and Stefan Zeugner

### See Also

`bms`

for creating `bma`

objects.

Check the appendix of `vignette(BMS)`

for a more detailed description of built-in priors.

Check http://bms.zeugner.eu/custompriors.php for examples.

[Package

*BMS* version 0.3.1

Index]