https://github.com/jhelvy/logitr
Fast estimation of multinomial (MNL) and mixed logit (MXL) models in R with "Preference" space or "Willingness-to-pay" (WTP) space utility parameterizations in R
https://github.com/jhelvy/logitr
log-likelihood logit logit-model mixed-logit mlogit multinomial-regression mxl mxl-models preference-space preferences r rstats rstats-package willingness-to-pay wtp
Last synced: 10 months ago
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Fast estimation of multinomial (MNL) and mixed logit (MXL) models in R with "Preference" space or "Willingness-to-pay" (WTP) space utility parameterizations in R
- Host: GitHub
- URL: https://github.com/jhelvy/logitr
- Owner: jhelvy
- License: other
- Created: 2014-11-03T11:29:27.000Z (over 11 years ago)
- Default Branch: master
- Last Pushed: 2024-11-01T19:42:12.000Z (over 1 year ago)
- Last Synced: 2025-03-28T19:12:30.877Z (about 1 year ago)
- Topics: log-likelihood, logit, logit-model, mixed-logit, mlogit, multinomial-regression, mxl, mxl-models, preference-space, preferences, r, rstats, rstats-package, willingness-to-pay, wtp
- Language: R
- Homepage: https://jhelvy.github.io/logitr/
- Size: 21.8 MB
- Stars: 56
- Watchers: 6
- Forks: 15
- Open Issues: 12
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- License: LICENSE
Awesome Lists containing this project
README
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
warning = FALSE,
message = FALSE,
comment = "#>",
fig.path = "man/figures/",
fig.retina = 3
)
```
# logitr 
[](https://CRAN.R-project.org/package=logitr)
[](https://app.travis-ci.com/github/jhelvy/logitr)
[](https://cran.r-project.org/package=logitr)
logitr: Fast Estimation of Multinomial (MNL) and Mixed Logit (MXL) Models with Preference Space and Willingness to Pay Space [Utility Parameterizations](https://jhelvy.github.io/logitr/articles/utility_models.html)
The latest version includes support for:
- Multinomial logit (MNL) models
- Mixed logit (MXL) models with normal and log-normal parameter distributions.
- Preference space and WTP space utility parameterizations.
- Weighted models to differentially weight individual observations.
- Uncorrelated or correlated heterogeneity covariances for mixed logit models.
- Functions for computing WTP from preference space models.
- Functions for predicting expected probabilities and outcomes for sets of alternatives based on an estimated model.
- A parallelized 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).
Mixed logit models 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)*](https://eml.berkeley.edu/books/choice2.html).
## Basic Usage
View the [basic usage](https://jhelvy.github.io/logitr/articles/basic_usage.html) page for details on how to use **logitr** to estimate models.
## JSS Article
An associated paper in the *Journal of Statistical Software* about this package is available at
[https://doi.org/10.18637/jss.v105.i10](https://doi.org/10.18637/jss.v105.i10)
## Installation
```{r child="man/rmdchunks/installation.Rmd"}
```
## Author, Version, and License Information
- Author: *John Paul Helveston* https://www.jhelvy.com/
- Date First Written: *Sunday, September 28, 2014*
- License: [MIT](https://github.com/jhelvy/logitr/blob/master/LICENSE.md)
## Citation Information
If you use this package for in a publication, please cite the JSS article associated with it! You can get the citation by typing `citation("logitr")` into R:
```{r}
citation("logitr")
```