apollo_makeHessian

Creates hessian function from the likelihood function apollo_probabilities provided by the user. Returns NULL if 
the creation of gradient function fails.

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
<http://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_makeHessian function

<dl><dt>apollo_beta</dt>
<dd>Named numeric vector. Names and values for (all) parameters.</dd>
<dt>apollo_fixed</dt>
<dd>Character vector. Names (as defined in <code>apollo_beta</code>) of parameters whose value should not 
change during estimation.</dd>
<dt>apollo_logLike</dt>
<dd>Function to calculate the log-likelihood of the model, as created by apollo_makeLogLike
If provided, the value of the analytical gradient will be compared to the value of the
numerical gradient as calculated using apollo_logLike and the numDeriv package.
If the difference between the two is bigger than 1
that the analytical gradient is wrong and NULL will be returned.</dd></dl>

Arguments

Creates hessian function. — apollo_makeHessian

<dl>

<dt>apollo_beta</dt>
<dd>Named numeric vector. Names and values for (all) parameters.</dd>


<dt>apollo_fixed</dt>
<dd>Character vector. Names (as defined in <code>apollo_beta</code>) of parameters whose value should not 
change during estimation.</dd>


<dt>apollo_logLike</dt>
<dd>Function to calculate the log-likelihood of the model, as created by apollo_makeLogLike
If provided, the value of the analytical gradient will be compared to the value of the
numerical gradient as calculated using apollo_logLike and the numDeriv package.
If the difference between the two is bigger than 1
that the analytical gradient is wrong and NULL will be returned.</dd>

</dl>

apollo_makeHessian: Creates hessian function.

Description

Usage

Value

Arguments

Details