Fast estimation of multinomial (MNL) and mixed logit (MXL) models in R with “Preference” space or “Willingness-to-pay” (WTP) space utility parameterizations.

• Homogeneous multinomial logit (MNL) models
• Heterogeneous mixed logit (MXL) models with normal and log-normal parameter distributions.
• Preference space and WTP space utility parameterizations.
• Weighted models to differentially weight individual choice observations.
• Functions for computing WTP from preference space models.
• Functions for predicting expected choices and choice probabilities for a set (or multiple sets) of alternatives based on an estimated model.
• An option to run a multistart optimization loop that uses different random starting points in each iteration to search for different local minima (useful for non-convex problems like MXL models or models with WTP space parameterizations).

Note: MXL models assume uncorrelated heterogeneity covariances and are estimated using maximum simulated likelihood based on the algorithms in Kenneth Train’s book Discrete Choice Methods with Simulation, 2nd Edition (New York: Cambridge University Press, 2009).

## Installation

You can install {logitr} from CRAN:

install.packages("logitr")

or you can install the development version of {logitr} from GitHub:

# install.packages("remotes")
remotes::install_github("jhelvy/logitr")

library(logitr)

## Basic Usage

View the basic usage page for details on how to use logitr to estimate models.

## Citation Information

If you use this package for in a publication, I would greatly appreciate it if you cited it - you can get the citation by typing citation("logitr") into R:

citation("logitr")
#>
#> To cite logitr in publications use:
#>
#>   John Paul Helveston (2021). logitr: Random utility logit models with
#>   preference and willingness to pay space parameterizations. R package
#>   version 0.3.1
#>
#> A BibTeX entry for LaTeX users is
#>
#>   @Manual{,
#>     title = {logitr: Random Utility Logit Models with Preference and Willingness to Pay Space Parameterizations},
#>     author = {John Paul Helveston},
#>     year = {2021},
#>     note = {R package version 0.3.1},
#>     url = {https://jhelvy.github.io/logitr/},
#>   }