logitr: Logit Models w/Preference & WTP Space Utility Parameterizations

Fast estimation of multinomial (MNL) and mixed logit (MXL) models in R. Models can be estimated using "Preference" space or "Willingness-to-pay" (WTP) space utility parameterizations. Weighted models can also be estimated. An option is available to run a parallelized multistart optimization loop with random starting points in each iteration, which is useful for non-convex problems like MXL models or models with WTP space utility parameterizations. The main optimization loop uses the 'nloptr' package to minimize the negative log-likelihood function. Additional functions are available for computing and comparing WTP from both preference space and WTP space models and for predicting expected choices and choice probabilities for sets of alternatives based on an estimated model. MXL models assume uncorrelated heterogeneity covariances and are estimated using maximum simulated likelihood based on the algorithms in Train (2009) "Discrete Choice Methods with Simulation, 2nd Edition" <doi:10.1017/CBO9780511805271>.

Package details

AuthorJohn Helveston [aut, cre, cph] (<https://orcid.org/0000-0002-2657-9191>), Connor Forsythe [ctb]
MaintainerJohn Helveston <john.helveston@gmail.com>
LicenseMIT + file LICENSE
Version0.5.0
URL https://github.com/jhelvy/logitr
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("logitr")

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logitr documentation built on Jan. 5, 2022, 1:08 a.m.