create_lagged_cov

This function creates lagged choice covariates from the <code>data.frame</code>
<code>choice_data</code>, which is assumed to be sorted by the choice occasions.

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

create_lagged_cov function

<dl><dt>choice_data</dt>
<dd>[<code>data.frame</code>] 
Choice data in wide format, where each row represents one choice occasion.</dd>
<dt>column</dt>
<dd>[<code><a href="/link/character()?package=RprobitB&version=1.2.0" data-mini-rdoc="RprobitB::character()">character()</a></code>] 
Covariate names in <code>choice_data</code>.</dd>
<dt>k</dt>
<dd>[<code><a href="/link/integer()?package=RprobitB&version=1.2.0" data-mini-rdoc="RprobitB::integer()">integer()</a></code>] 
The number of lags (in units of observations), see the details.</dd>
<dt>id</dt>
<dd>[<code>character(1)</code>] 
The name of the column in <code>choice_data</code> that contains unique identifier
for each decision maker.</dd></dl>

Arguments

Create lagged choice covariates — create_lagged_cov

<dl>

<dt>choice_data</dt>
<dd>[<code>data.frame</code>] 
Choice data in wide format, where each row represents one choice occasion.</dd>


<dt>column</dt>
<dd>[<code><a href='https://rdrr.io/r/base/character.html'>character()</a></code>] 
Covariate names in <code>choice_data</code>.</dd>


<dt>k</dt>
<dd>[<code><a href='https://rdrr.io/r/base/integer.html'>integer()</a></code>] 
The number of lags (in units of observations), see the details.</dd>


<dt>id</dt>
<dd>[<code>character(1)</code>] 
The name of the column in <code>choice_data</code> that contains unique identifier
for each decision maker.</dd>

</dl>

create_lagged_cov: Create lagged choice covariates

Description

Usage

Value

Arguments

Details

Examples