Package: mixl 1.3.3

mixl: Simulated Maximum Likelihood Estimation of Mixed Logit Models for Large Datasets

Specification and estimation of multinomial logit models. Large datasets and complex models are supported, with an intuitive syntax. Multinomial Logit Models, Mixed models, random coefficients and Hybrid Choice are all supported. For more information, see Molloy et al. (2019) <doi:10.3929/ethz-b-000334289>.

Authors:Joseph Molloy [aut, cre]

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mixl.pdf |mixl.html✨
mixl/json (API)

# Install 'mixl' in R:
install.packages('mixl', repos = c('https://joemolloy.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/joemolloy/fast-mixed-mnl/issues

On CRAN:

Conda:

4.78 score 4 stars 8 scripts 892 downloads 12 exports 38 dependencies

Last updated 7 days agofrom:62a586e837. Checks:1 OK, 11 WARNING. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 27 2025
R-4.5-win-x86_64WARNINGMar 27 2025
R-4.5-mac-x86_64WARNINGMar 27 2025
R-4.5-mac-aarch64WARNINGMar 27 2025
R-4.5-linux-x86_64WARNINGMar 27 2025
R-4.4-win-x86_64WARNINGMar 27 2025
R-4.4-mac-x86_64WARNINGMar 27 2025
R-4.4-mac-aarch64WARNINGMar 27 2025
R-4.4-linux-x86_64WARNINGMar 27 2025
R-4.3-win-x86_64WARNINGMar 27 2025
R-4.3-mac-x86_64WARNINGMar 27 2025
R-4.3-mac-aarch64WARNINGMar 27 2025

Exports:av_matrixcompileUtilityFunctioncreate_halton_drawsestimateextract_av_colsextract_indiv_datagenerate_default_availabilitiesposteriorsprobabilitiesspecify_modelsummary_texutilities

Dependencies:bitbit64clicliprcpp11crayondigestfansigenericsgluehmslatticelifecyclemagrittrmaxLikmiscToolsnumDerivpillarpkgconfigprettyunitsprogressR6randtoolboxRcppreadrrlangrngWELLsandwichstringistringrtibbletidyselecttzdbutf8vctrsvroomwithrzoo

Mixl User Guide

Joe Molloy

Rendered fromuser-guide.Rmdusingknitr::rmarkdownon Mar 27 2025.

Last update: 2021-02-26
Started: 2019-02-14