# posterior-methods: Sample from the posterior distribution of one of several... In BayesFactor: Computation of Bayes Factors for Common Designs

 posterior R Documentation

## Sample from the posterior distribution of one of several models.

### Description

This function samples from the posterior distribution of a `BFmodel`, which can be obtained from a `BFBayesFactor` object. If there is more than one numerator in the `BFBayesFactor` object, the `index` argument can be passed to select one numerator.

### Usage

``````posterior(model, index, data, iterations, ...)

## S4 method for signature 'BFmodel,missing,data.frame,missing'
posterior(model, index, data, iterations, ...)

## S4 method for signature 'BFBayesFactor,missing,missing,missing'
posterior(model, index, data, iterations, ...)

## S4 method for signature 'BFBayesFactor,numeric,missing,numeric'
posterior(model, index, data, iterations, ...)

## S4 method for signature 'BFBayesFactor,missing,missing,numeric'
posterior(model, index = NULL, data, iterations, ...)

## S4 method for signature 'BFlinearModel,missing,data.frame,numeric'
posterior(model, index = NULL, data, iterations, ...)

## S4 method for signature 'BFindepSample,missing,data.frame,numeric'
posterior(model, index = NULL, data, iterations, ...)

## S4 method for signature 'BFcontingencyTable,missing,data.frame,numeric'
posterior(model, index = NULL, data, iterations, ...)

## S4 method for signature 'BFoneSample,missing,data.frame,numeric'
posterior(model, index = NULL, data, iterations, ...)

## S4 method for signature 'BFmetat,missing,data.frame,numeric'
posterior(model, index = NULL, data, iterations, ...)

## S4 method for signature 'BFproportion,missing,data.frame,numeric'
posterior(model, index = NULL, data, iterations, ...)

## S4 method for signature 'BFcorrelation,missing,data.frame,numeric'
posterior(model, index = NULL, data, iterations, ...)
``````

### Arguments

 `model` or set of models from which to sample `index` the index within the set of models giving the desired model `data` the data to be conditioned on `iterations` the number of iterations to sample `...` arguments passed to and from related methods

### Details

The data argument is used internally, and will y not be needed by end-users.

Note that if there are fixed effects in the model, the reduced parameterzation used internally (see help for `anovaBF`) is unreduced. For a factor with two levels, the chain will contain two effect estimates that sum to 0.

Two useful arguments that can be passed to related methods are `thin` and `columnFilter`, currently implemented for methods using `nWayAOV` (models with more than one categorical covariate, or a mix of categorical and continuous covariates). `thin`, an integer, will keep only every `thin` iterations. The default is `thin=1`, which keeps all iterations. Argument `columnFilter` is either `NULL` (for no filtering) or a character vector of extended regular expressions (see regex help for details). Any column from an effect that matches one of the filters will not be saved.

### Value

Returns an object containing samples from the posterior distribution of the specified model

### Examples

``````## Sample from the posteriors for two models
data(sleep)

bf = lmBF(extra ~ group + ID, data = sleep, whichRandom="ID", progress=FALSE)

## sample from the posterior of the numerator model
## data argument not needed - it is included in the Bayes factor object
chains = posterior(bf, iterations = 1000, progress = FALSE)

plot(chains)

## demonstrate column filtering by filtering out participant effects
data(puzzles)
bf = lmBF(RT ~ shape + color + shape:color + ID, data=puzzles)
chains = posterior(bf, iterations = 1000, progress = FALSE, columnFilter="^ID\$")
colnames(chains) # Contains no participant effects
``````

BayesFactor documentation built on May 29, 2024, 3:09 a.m.