apollo_lcUnconditionals

Returns values for random parameters and class allocation probabilities in a latent class model model.

Choice models are a widely used technique across numerous scientific disciplines. The Apollo package is a very flexible tool for the estimation and application
of choice models in R. Users are able to write their own
model functions or use a mix of already available ones. Random heterogeneity,
both continuous and discrete and at the level of individuals and
choices, can be incorporated for all models. There is support for both standalone
models and hybrid model structures. Both classical
and Bayesian estimation is available, and multiple discrete
continuous models are covered in addition to discrete choice.
Multi-threading processing is supported for estimation and a large
number of pre and post-estimation routines, including for computing posterior
(individual-level) distributions are available.
For examples, a manual, and a support forum, visit
<https://www.ApolloChoiceModelling.com>. For more information on choice
models see Train, K. (2009) <isbn:978-0-521-74738-7> and Hess,
S. & Daly, A.J. (2014) <isbn:978-1-781-00314-5> for an overview
of the field.

Stephane Hess

apollo

Tools for Choice Model Estimation and Application

David Palma

Thomas Hancock

apollo_lcUnconditionals function

<dl><dt>model</dt>
<dd>Model object. Estimated model object as returned by function apollo_estimate.</dd>
<dt>apollo_probabilities</dt>
<dd>Function. Returns probabilities of the model to be estimated. Must receive three arguments:<ul>
<li><code>apollo_beta</code>: Named numeric vector. Names and values of model parameters.</li>
<li><code>apollo_inputs</code>: List containing options of the model. See apollo_validateInputs.</li>
<li><code>functionality</code>: Character. Can be either <code>"components"</code>, <code>"conditionals"</code>, <code>"estimate"</code> (default), <code>"gradient"</code>, <code>"hessian"</code>, <code>"output"</code>, <code>"prediction"</code>, <code>"preprocess"</code>, <code>"raw"</code>, <code>"report"</code>, <code>"shares_LL"</code>, <code>"validate"</code> or <code>"zero_LL"</code>.</li>
</ul></dd>
<dt>apollo_inputs</dt>
<dd>List grouping most common inputs. Created by function apollo_validateInputs.</dd></dl>

Arguments

Returns unconditionals for a latent class model — apollo_lcUnconditionals

<dl>

<dt>model</dt>
<dd>Model object. Estimated model object as returned by function apollo_estimate.</dd>


<dt>apollo_probabilities</dt>
<dd>Function. Returns probabilities of the model to be estimated. Must receive three arguments:<ul>
<li><code>apollo_beta</code>: Named numeric vector. Names and values of model parameters.</li>
<li><code>apollo_inputs</code>: List containing options of the model. See apollo_validateInputs.</li>
<li><code>functionality</code>: Character. Can be either <code>"components"</code>, <code>"conditionals"</code>, <code>"estimate"</code> (default), <code>"gradient"</code>, <code>"hessian"</code>, <code>"output"</code>, <code>"prediction"</code>, <code>"preprocess"</code>, <code>"raw"</code>, <code>"report"</code>, <code>"shares_LL"</code>, <code>"validate"</code> or <code>"zero_LL"</code>.</li>
</ul></dd>


<dt>apollo_inputs</dt>
<dd>List grouping most common inputs. Created by function apollo_validateInputs.</dd>

</dl>

apollo_lcUnconditionals: Returns unconditionals for a latent class model

Description

Usage

Value

Arguments