brmsfit_needs_refit

Checks whether a given cached fit can be used without refitting when
<code>file_refit = "on_change"</code> is used.
This function is internal and exposed only to facilitate debugging problems
with cached fits. The function may change or be removed in future versions
and scripts should not use it.

internal

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

Mattan S. Ben-Shachar

Hayden Rabel

Simon C. Mills

Stephen Wild

brmsfit_needs_refit function

<dl><dt>fit</dt>
<dd>Old <code>brmsfit</code> object (e.g., loaded from file).</dd>
<dt>sdata</dt>
<dd>New Stan data (result of a call to <code>make_standata</code>).
Pass <code>NULL</code> to avoid this data check.</dd>
<dt>scode</dt>
<dd>New Stan code (result of a call to <code>make_stancode</code>).
Pass <code>NULL</code> to avoid this code check.</dd>
<dt>data</dt>
<dd>New data to check consistency of factor level names.
Pass <code>NULL</code> to avoid this data check.</dd>
<dt>algorithm</dt>
<dd>New algorithm. Pass <code>NULL</code> to avoid algorithm check.</dd>
<dt>silent</dt>
<dd>Logical. If <code>TRUE</code>, no messages will be given.</dd>
<dt>verbose</dt>
<dd>Logical. If <code>TRUE</code> detailed report of the differences
is printed to the console.</dd></dl>

Arguments

Check if cached fit can be used. — brmsfit_needs_refit

<dl>

<dt>fit</dt>
<dd>Old <code>brmsfit</code> object (e.g., loaded from file).</dd>


<dt>sdata</dt>
<dd>New Stan data (result of a call to <code>make_standata</code>).
Pass <code>NULL</code> to avoid this data check.</dd>


<dt>scode</dt>
<dd>New Stan code (result of a call to <code>make_stancode</code>).
Pass <code>NULL</code> to avoid this code check.</dd>


<dt>data</dt>
<dd>New data to check consistency of factor level names.
Pass <code>NULL</code> to avoid this data check.</dd>


<dt>algorithm</dt>
<dd>New algorithm. Pass <code>NULL</code> to avoid algorithm check.</dd>


<dt>silent</dt>
<dd>Logical. If <code>TRUE</code>, no messages will be given.</dd>


<dt>verbose</dt>
<dd>Logical. If <code>TRUE</code> detailed report of the differences
is printed to the console.</dd>

</dl>

Check if cached fit can be used.

brmsfit_needs_refit: Check if cached fit can be used.

Description

Usage

Value

Arguments

Details