apollo_basTest

Either a character variable with the name of a previously estimated model, or an estimated 
model in memory, as returned by <a rd-options="" href="/link/apollo_estimate?package=apollo&version=0.2.6" data-mini-rdoc="apollo::apollo_estimate">apollo_estimate</a>.

model1

model2

Calculates the p-value for the Ben-Akiva &amp; Swait test for non-nested models. 
The two models need to both be discrete choice, and estimated on the same data.

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
<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.

David Palma

apollo

Tools for Choice Model Estimation and Application

Stephane Hess

Thomas Hancock

apollo_basTest function

Either a character variable with the name of a previously estimated model, or an estimated 
model in memory, as returned by <a rd-options='' href='apollo_estimate'>apollo_estimate</a>.

apollo_basTest: Ben-Akiva & Swait test

Description

Usage

Arguments

Value