R: Prepare Predictions

prepare_predictions.brmsfit {brms} | R Documentation

## Prepare Predictions

### Description

This method helps in preparing brms models for certin post-processing tasks most notably various forms of predictions. Unless you are a package developer, you will rarely need to call `prepare_predictions` directly.

### Usage

    ## S3 method for class 'brmsfit'
    prepare_predictions(
      x,
      newdata = NULL,
      re_formula = NULL,
      allow_new_levels = FALSE,
      sample_new_levels = "uncertainty",
      incl_autocor = TRUE,
      oos = NULL,
      resp = NULL,
      ndraws = NULL,
      draw_ids = NULL,
      nsamples = NULL,
      subset = NULL,
      nug = NULL,
      smooths_only = FALSE,
      offset = TRUE,
      newdata2 = NULL,
      new_objects = NULL,
      point_estimate = NULL,
      ...
    )

    prepare_predictions(x, ...)

### Arguments

`x` | An R object typically of class `'brmsfit'`.
`newdata` | An optional data.frame for which to evaluate predictions. If `NULL` (default), the original data of the model is used. `NA` values within factors are interpreted as if all dummy variables of this factor are zero. This allows, for instance, to make predictions of the grand mean when using sum coding.
`re_formula` | formula containing group-level effects to be considered in the prediction. If `NULL` (default), include all group-level effects; if `NA`, include no group-level effects.
`allow_new_levels` | A flag indicating if new levels of group-level effects are allowed (defaults to `FALSE`). Only relevant if `newdata` is provided.
`sample_new_levels` | Indicates how to sample new levels for grouping factors specified in `re_formula`. This argument is only relevant if `newdata` is provided and `allow_new_levels` is set to `TRUE`. If `"uncertainty"` (default), each posterior sample for a new level is drawn from the posterior draws of a randomly chosen existing level. Each posterior sample for a new level may be drawn from a different existing level such that the resulting set of new posterior draws represents the variation across existing levels. If `"gaussian"`, sample new levels from the (multivariate) normal distribution implied by the group-level standard deviations and correlations. This options may be useful for conducting Bayesian power analysis or predicting new levels in situations where relatively few levels where observed in the old_data. If `"old_levels"`, directly sample new levels from the existing levels, where a new level is assigned all of the posterior draws of the same (randomly chosen) existing level.
`incl_autocor` | A flag indicating if correlation structures originally specified via `autocor` should be included in the predictions. Defaults to `TRUE`.
`oos` | Optional indices of observations for which to compute out-of-sample rather than in-sample predictions. Only required in models that make use of response values to make predictions, that is, currently only ARMA models.
`resp` | Optional names of response variables. If specified, predictions are performed only for the specified response variables.
`ndraws` | Positive integer indicating how many posterior draws should be used. If `NULL` (the default) all draws are used. Ignored if `draw_ids` is not `NULL`.
`draw_ids` | An integer vector specifying the posterior draws to be used. If `NULL` (the default), all draws are used.
`nsamples` | Deprecated alias of `ndraws`.
`subset` | Deprecated alias of `draw_ids`.
`nug` | Small positive number for Gaussian process terms only. For numerical reasons, the covariance matrix of a Gaussian process might not be positive definite. Adding a very small number to the matrix's diagonal often solves this problem. If `NULL` (the default), `nug` is chosen internally.
`smooths_only` | Logical; If `TRUE` only predictions related to the
`offset` | Logical; Indicates if offsets should be included in the predictions. Defaults to `TRUE`.
`newdata2` | A named `list` of objects containing new data, which cannot be passed via argument `newdata`. Required for some objects used in autocorrelation structures, or `stanvars`.
`new_objects` | Deprecated alias of `newdata2`.
`point_estimate` | Shall the returned object contain only point estimates of the parameters instead of their posterior draws? Defaults to `NULL` in which case no point estimate is computed. Alternatively, may be set to `"mean"` or `"median"`. This argument is primarily implemented to ensure compatibility with the `loo_subsample` method.
`...` | Further arguments passed to `validate_newdata`.

### Value

An object of class `'brmsprep'` or `'mvbrmsprep'`, depending on whether a univariate or multivariate model is passed.

[Package brms version 2.17.0 Index]