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logitr  

Logit Models w/Preference & WTP Space Utility Parameterizations
View on CRAN: Click here


Download and install logitr package within the R console
Install from CRAN:
install.packages("logitr")

Install from Github:
library("remotes")
install_github("cran/logitr")

Install by package version:
library("remotes")
install_version("logitr", "1.1.2")



Attach the package and use:
library("logitr")
Maintained by
John Helveston
[Scholar Profile | Author Map]
First Published: 2021-01-19
Latest Update: 2023-05-17
Description:
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. Mixed logit models can include uncorrelated or correlated heterogeneity covariances and are estimated using maximum simulated likelihood based on the algorithms in Train (2009) . More details can be found in Helveston (2023) .
How to cite:
John Helveston (2021). logitr: Logit Models w/Preference & WTP Space Utility Parameterizations. R package version 1.1.2, https://cran.r-project.org/web/packages/logitr. Accessed 02 May. 2025.
Previous versions and publish date:
0.1.0 (2021-01-19 09:40), 0.2.0 (2021-06-14 15:50), 0.3.0 (2021-08-13 20:20), 0.4.0 (2021-10-25 19:30), 0.5.0 (2022-01-04 22:40), 0.6.0 (2022-06-11 12:50), 0.6.1 (2022-06-12 17:50), 0.7.0 (2022-06-17 00:40), 0.8.0 (2022-10-03 22:30), 1.0.0 (2023-02-07 09:22), 1.0.1 (2023-02-19 14:00), 1.1.0 (2023-05-18 00:00), 1.1.1 (2023-09-29 17:40)
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