R: Create a summary of a fitted model represented by a 'brmsfit'...

summary.brmsfit {brms} | R Documentation

## Create a summary of a fitted model represented by a `brmsfit` object

### Description

Create a summary of a fitted model represented by a `brmsfit` object

### Usage

    ## S3 method for class 'brmsfit'
    summary(
      object,
      priors = FALSE,
      prob = 0.95,
      robust = FALSE,
      mc_se = FALSE,
      ...
    )

### Arguments

`object` | An object of class `brmsfit`.
`priors` | Logical; Indicating if priors should be included in the summary. Default is `FALSE`.
`prob` | A value between 0 and 1 indicating the desired probability to be covered by the uncertainty intervals. The default is 0.95.
`robust` | If `FALSE` (the default) the mean is used as the measure of central tendency and the standard deviation as the measure of variability. If `TRUE`, the median and the median absolute deviation (MAD) are applied instead.
`mc_se` | Logical; Indicating if the uncertainty in `Estimate` caused by the MCMC sampling should be shown in the summary. Defaults to `FALSE`.
`...` | Other potential arguments

### Details

The convergence diagnostics `Rhat`, `Bulk_ESS`, and `Tail_ESS` are described in detail in Vehtari et al. (2020).

### References

Aki Vehtari, Andrew Gelman, Daniel Simpson, Bob Carpenter, and Paul-Christian Bürkner (2020). Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC. *Bayesian Analysis*. 1–28. dpi:10.1214/20-BA1221

[Package brms version 2.17.0 Index]