R: Posterior draws of parameters averaged across models

posterior_average.brmsfit {brms} | R Documentation

## Posterior draws of parameters averaged across models

### Description

Extract posterior draws of parameters averaged across models. Weighting can be done in various ways, for instance using Akaike weights based on information criteria or marginal likelihoods.

### Usage

    ## S3 method for class 'brmsfit'
    posterior_average(
      x,
      ...,
      variable = NULL,
      pars = NULL,
      weights = "stacking",
      ndraws = NULL,
      nsamples = NULL,
      missing = NULL,
      model_names = NULL,
      control = list(),
      seed = NULL
    )

    posterior_average(x, ...)

### Arguments

`x` | A `brmsfit` object.
`...` | More `brmsfit` objects or further arguments passed to the underlying post-processing functions. In particular, see `prepare_predictions` for further supported arguments.
`variable` | Names of variables (parameters) for which to average across models. Only those variables can be averaged that appear in every model. Defaults to all overlapping variables.
`pars` | Deprecated alias of `variable`.
`weights` | Name of the criterion to compute weights from. Should be one of `"loo"`, `"waic"`, `"kfold"`, `"stacking"` (current default), or `"bma"`, `"pseudobma"`, For the former three options, Akaike weights will be computed based on the information criterion values returned by the respective methods. For `"stacking"` and `"pseudobma"`, method `loo_model_weights` will be used to obtain weights. For `"bma"`, method `post_prob` will be used to compute Bayesian model averaging weights based on log marginal likelihood values (make sure to specify reasonable priors in this case). For some methods, `weights` may also be a numeric vector of pre-specified weights.
`ndraws` | Total number of posterior draws to use.
`nsamples` | Deprecated alias of `ndraws`.
`missing` | An optional numeric value or a named list of numeric values to use if a model does not contain a variable for which posterior draws should be averaged. Defaults to `NULL`, in which case only those variables can be averaged that are present in all of the models.
`model_names` | If `NULL` (the default) will use model names derived from deparsing the call. Otherwise will use the passed values as model names.
`control` | Optional `list` of further arguments passed to the function specified in `weights`.
`seed` | A single numeric value passed to `set.seed` to make results reproducible.

### Details

Weights are computed with the `model_weights` method.

### Value

A `data.frame` of posterior draws.

### See Also

`model_weights`, `pp_average`

### Examples

    ## Not run:
    # model with 'treat' as predictor
    fit1 <- brm(rating ~ treat + period + carry, data = inhaler)
    summary(fit1)

    # model without 'treat' as predictor
    fit2 <- brm(rating ~ period + carry, data = inhaler)
    summary(fit2)

    # compute model-averaged posteriors of overlapping parameters
    posterior_average(fit1, fit2, weights = "waic")

    ## End(Not run)

[Package brms version 2.16.1 Index]