transform.RprobitB_fit

Given an object of class <code>RprobitB_fit</code>, this function can:<ul>
<li>change the length <code>B</code> of the burn-in period,</li>
<li>change the the thinning factor <code>Q</code> of the Gibbs samples,</li>
<li>change the utility <code>scale</code>.</li>
</ul>

Bayes estimation of probit choice models in cross-sectional and panel
settings. The package can analyze binary, multivariate, ordered, and ranked
choices, as well as heterogeneity of choice behavior among deciders. The
main functionality includes model fitting via Gibbs sampling, tools for
convergence diagnostic, choice data simulation, in-sample and out-of-sample
choice prediction, and model selection using information criteria and Bayes
factors. The latent class model extension facilitates preference-based
decider classification, where the number of latent classes can be inferred
via the Dirichlet process or a weight-based updating heuristic. This allows
for flexible modeling of choice behavior without the need to impose
structural constraints. For a reference on the method, see Oelschlaeger and
Bauer (2021) <https://trid.trb.org/view/1759753>.

Lennart Oelschläger

RprobitB

Bayesian Probit Choice Modeling

Dietmar Bauer

transform.RprobitB_fit function

<dl><dt>_data</dt>
<dd>An object of class <code>RprobitB_fit</code>.</dd>
<dt>B</dt>
<dd>[<code>integer(1)</code>] 
The length of the burn-in period.</dd>
<dt>Q</dt>
<dd>[<code>integer(1)</code>] 
The thinning factor for the Gibbs samples.</dd>
<dt>scale</dt>
<dd>[<code>character(1)</code>] 
A character which determines the utility scale. It is of the form
<code>&lt;parameter&gt; := &lt;value&gt;</code>, where <code>&lt;parameter&gt;</code> is either the name of a fixed
effect or <code>Sigma_&lt;j&gt;,&lt;j&gt;</code> for the <code>&lt;j&gt;</code>th diagonal element of <code>Sigma</code>, and
<code>&lt;value&gt;</code> is the value of the fixed parameter.</dd>
<dt>check_preference_flip</dt>
<dd>Set to <code>TRUE</code> to check for flip in preferences after new <code>scale</code>.</dd>
<dt>...</dt>
<dd>Currently not used.</dd></dl>

Arguments

Transform fitted probit model — transform.RprobitB_fit

<dl>

<dt>_data</dt>
<dd>An object of class <code>RprobitB_fit</code>.</dd>


<dt>B</dt>
<dd>[<code>integer(1)</code>] 
The length of the burn-in period.</dd>


<dt>Q</dt>
<dd>[<code>integer(1)</code>] 
The thinning factor for the Gibbs samples.</dd>


<dt>scale</dt>
<dd>[<code>character(1)</code>] 
A character which determines the utility scale. It is of the form
<code>&lt;parameter&gt; := &lt;value&gt;</code>, where <code>&lt;parameter&gt;</code> is either the name of a fixed
effect or <code>Sigma_&lt;j&gt;,&lt;j&gt;</code> for the <code>&lt;j&gt;</code>th diagonal element of <code>Sigma</code>, and
<code>&lt;value&gt;</code> is the value of the fixed parameter.</dd>


<dt>check_preference_flip</dt>
<dd>Set to <code>TRUE</code> to check for flip in preferences after new <code>scale</code>.</dd>


<dt>...</dt>
<dd>Currently not used.</dd>

</dl>

transform.RprobitB_fit: Transform fitted probit model

Description

Usage

Value

Arguments

Details