add_loo

add_waic

add_ic

add_ic.brmsfit

add_ic&lt;-

Deprecated aliases of <code>add_criterion</code>.

Fit Bayesian generalized (non-)linear multivariate multilevel models
using 'Stan' for full Bayesian inference. A wide range of distributions
and link functions are supported, allowing users to fit -- among others --
linear, robust linear, count data, survival, response times, ordinal,
zero-inflated, hurdle, and even self-defined mixture models all in a
multilevel context. Further modeling options include both theory-driven and
data-driven non-linear terms, auto-correlation structures, censoring and
truncation, meta-analytic standard errors, and quite a few more.
In addition, all parameters of the response distribution can be predicted
in order to perform distributional regression. Prior specifications are
flexible and explicitly encourage users to apply prior distributions that
actually reflect their prior knowledge. Models can easily be evaluated and
compared using several methods assessing posterior or prior predictions.
References: Bürkner (2017) <doi:10.18637/jss.v080.i01>;
Bürkner (2018) <doi:10.32614/RJ-2018-017>;
Bürkner (2021) <doi:10.18637/jss.v100.i05>; Carpenter et al. (2017)
<doi:10.18637/jss.v076.i01>.

PaulChristian Buerkner

brms

Bayesian Regression Models using 'Stan'

Paul-Christian Bürkner

Jonah Gabry

Sebastian Weber

Andrew Johnson

Martin Modrak

Hamada S. Badr

Frank Weber

Aki Vehtari

Mattan S. Ben-Shachar

Hayden Rabel

Simon C. Mills

Stephen Wild

Ven Popov

add_loo function

<dl><dt>x</dt>
<dd>An R object typically of class <code>brmsfit</code>.</dd>
<dt>model_name</dt>
<dd>Optional name of the model. If <code>NULL</code>
(the default) the name is taken from the call to <code>x</code>.</dd>
<dt>...</dt>
<dd>Further arguments passed to the underlying
functions computing the model fit criteria. If you are recomputing
an already stored criterion with other <code>...</code> arguments, make
sure to set <code>overwrite = TRUE</code>.</dd>
<dt>ic, value</dt>
<dd>Names of model fit criteria
to compute. Currently supported are <code>"loo"</code>,
<code>"waic"</code>, <code>"kfold"</code>, <code>"R2"</code> (R-squared), and
<code>"marglik"</code> (log marginal likelihood).</dd></dl>

Arguments

Add model fit criteria to model objects — add_loo

<dl>

<dt>x</dt>
<dd>An R object typically of class <code>brmsfit</code>.</dd>


<dt>model_name</dt>
<dd>Optional name of the model. If <code>NULL</code>
(the default) the name is taken from the call to <code>x</code>.</dd>


<dt>...</dt>
<dd>Further arguments passed to the underlying
functions computing the model fit criteria. If you are recomputing
an already stored criterion with other <code>...</code> arguments, make
sure to set <code>overwrite = TRUE</code>.</dd>


<dt>ic, value</dt>
<dd>Names of model fit criteria
to compute. Currently supported are <code>"loo"</code>,
<code>"waic"</code>, <code>"kfold"</code>, <code>"R2"</code> (R-squared), and
<code>"marglik"</code> (log marginal likelihood).</dd>

</dl>

Add model fit criteria to model objects

add_loo: Add model fit criteria to model objects

Description

Usage

Value

Arguments