R: Extract Model Coefficients

coef.brmsfit {brms} | R Documentation

## Extract Model Coefficients

### Description

Extract model coefficients, which are the sum of population-level effects and corresponding group-level effects

### Usage

    ## S3 method for class 'brmsfit'
    coef(object, summary = TRUE, robust = FALSE, probs = c(0.025, 0.975), ...)

### Arguments

`object` | An object of class `brmsfit`.
`summary` | Should summary statistics be returned instead of the raw values? Default is `TRUE`.
`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. Only used if `summary` is `TRUE`.
`probs` | The percentiles to be computed by the `quantile` function. Only used if `summary` is `TRUE`.
`...` | Further arguments passed to `fixef.brmsfit` and `ranef.brmsfit`.

### Value

A list of 3D arrays (one per grouping factor). If `summary` is `TRUE`, the 1st dimension contains the factor levels, the 2nd dimension contains the summary statistics (see `posterior_summary`), and the 3rd dimension contains the group-level effects. If `summary` is `FALSE`, the 1st dimension contains the posterior draws, the 2nd dimension contains the factor levels, and the 3rd dimension contains the group-level effects.

### Examples

    ## Not run:
    fit <- brm(count ~ zAge + zBase * Trt + (1+Trt|visit),
               data = epilepsy, family = gaussian(), chains = 2)
    ## extract population and group-level coefficients separately
    fixef(fit)
    ranef(fit)
    ## extract combined coefficients
    coef(fit)

    ## End(Not run)

[Package brms version 2.16.3 Index]