apollo_lcUnconditionals

Model object. Estimated model object as returned by function <a rd-options="" href="/link/apollo_estimate?package=apollo&version=0.1.0" data-mini-rdoc="apollo::apollo_estimate">apollo_estimate</a>.

model

Function. Returns probabilities of the model to be estimated. Must receive three arguments:<ul>
<li>apollo_beta: Named numeric vector. Names and values of model parameters.</li>
<li>apollo_inputs: List containing options of the model. See <a rd-options="" href="/link/apollo_validateInputs?package=apollo&version=0.1.0" data-mini-rdoc="apollo::apollo_validateInputs">apollo_validateInputs</a>.</li>
<li>functionality: Character. Can be either "estimate" (default), "prediction", "validate", "conditionals", "zero_LL", or "raw".</li>
</ul>

apollo_probabilities

List grouping most common inputs. Created by function <a rd-options="" href="/link/apollo_validateInputs?package=apollo&version=0.1.0" data-mini-rdoc="apollo::apollo_validateInputs">apollo_validateInputs</a>.

apollo_inputs

Returns draws (unconditionals) for random parameters in model, including interactions with deterministic covariates

The Choice Modelling Centre (CMC) at the University of Leeds
has developed flexible code 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
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.

David Palma

apollo

Tools for Choice Model Estimation and Application

Stephane Hess

apollo_lcUnconditionals function

Model object. Estimated model object as returned by function <a rd-options='' href='apollo_estimate'>apollo_estimate</a>.

Function. Returns probabilities of the model to be estimated. Must receive three arguments:<ul>
<li>apollo_beta: Named numeric vector. Names and values of model parameters.</li>
<li>apollo_inputs: List containing options of the model. See <a rd-options='' href='apollo_validateInputs'>apollo_validateInputs</a>.</li>
<li>functionality: Character. Can be either "estimate" (default), "prediction", "validate", "conditionals", "zero_LL", or "raw".</li>
</ul>

List grouping most common inputs. Created by function <a rd-options='' href='apollo_validateInputs'>apollo_validateInputs</a>.

apollo_lcUnconditionals: Returns draws for random parameters in a latent class model model

Description

Usage

Arguments

Value

Details