# log_lik.brmsfit

##### Compute the Pointwise Log-Likelihood

Compute the Pointwise Log-Likelihood

##### Usage

```
# S3 method for brmsfit
log_lik(object, newdata = NULL, re_formula = NULL,
resp = NULL, nsamples = NULL, subset = NULL, pointwise = FALSE,
combine = TRUE, ...)
```

##### Arguments

- object
A fitted model object of class

`brmsfit`

.- newdata
An optional data.frame for which to evaluate predictions. If

`NULL`

(default), the original data of the model is used.- 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.- resp
Optional names of response variables. If specified, predictions are performed only for the specified response variables.

- nsamples
Positive integer indicating how many posterior samples should be used. If

`NULL`

(the default) all samples are used. Ignored if`subset`

is not`NULL`

.- subset
A numeric vector specifying the posterior samples to be used. If

`NULL`

(the default), all samples are used.- pointwise
A flag indicating whether to compute the full log-likelihood matrix at once (the default), or just return the likelihood function along with all data and samples required to compute the log-likelihood separately for each observation. The latter option is rarely useful when calling

`log_lik`

directly, but rather when computing`waic`

or`loo`

.- combine
Only relevant in multivariate models. Indicates if the log-likelihoods of the submodels should be combined per observation (i.e. added together; the default) or if the log-likelihoods should be returned separately.

- ...
Further arguments passed to

`extract_draws`

that control several aspects of data validation and prediction.

##### Value

Usually, an S x N matrix containing the pointwise log-likelihood
samples, where S is the number of samples and N is the number
of observations in the data. For multivariate models and if
`combine`

is `FALSE`

, an S x N x R array is returned,
where R is the number of response variables.
If `pointwise = TRUE`

, the output is a function
with a `draws`

attribute containing all relevant
data and posterior samples.

*Documentation reproduced from package brms, version 2.9.0, License: GPL (>= 3)*