apollo_dVdB

Calculates gradients (derivatives) of utility functions.

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_dVdB function

<dl><dt>apollo_beta</dt>
<dd>Named numeric vector of parameters.</dd>
<dt>apollo_inputs</dt>
<dd>List grouping most common inputs. Created by function apollo_validateInputs.</dd>
<dt>V</dt>
<dd>Named list of functions. Each function defines the deterministic utility for one alternative.</dd></dl>

Arguments

Calculates gradients of utility functions — apollo_dVdB

<dl>

<dt>apollo_beta</dt>
<dd>Named numeric vector of parameters.</dd>


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


<dt>V</dt>
<dd>Named list of functions. Each function defines the deterministic utility for one alternative.</dd>

</dl>

apollo_dVdB: Calculates gradients of utility functions

Description

Usage

Value

Arguments