Package: ChoiceModelR 1.3.1

ChoiceModelR: Choice Modeling in R

Implements an MCMC algorithm to estimate a hierarchical multinomial logit model with a normal heterogeneity distribution. The algorithm uses a hybrid Gibbs Sampler with a random walk metropolis step for the MNL coefficients for each unit. Dependent variable may be discrete or continuous. Independent variables may be discrete or continuous with optional order constraints. Means of the distribution of heterogeneity can optionally be modeled as a linear function of unit characteristics variables.

Authors:Ryan Sermas [aut], John V Colias [ctb, cre], Decision Analyst, Inc. [cph]

ChoiceModelR_1.3.1.tar.gz
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ChoiceModelR_1.3.1.tgz(r-4.4-any)ChoiceModelR_1.3.1.tgz(r-4.3-any)
ChoiceModelR_1.3.1.tar.gz(r-4.5-noble)ChoiceModelR_1.3.1.tar.gz(r-4.4-noble)
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ChoiceModelR.pdf |ChoiceModelR.html✨
ChoiceModelR/json (API)
NEWS

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

Peer review:

Datasets:
  • datar - Arificial (Simulated) Choice Data for choicemodelr
  • sharedatar - Arificial (Simulated) Fractional Choice Data for choicemodelr
  • truebetas - True betas used to simulate data in the choice data set named datar, which is used in the example.

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.71 score 3 stars 34 scripts 802 downloads 1 mentions 1 exports 0 dependencies

Last updated 1 months agofrom:e1aac557a0. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 10 2024
R-4.5-winOKNov 10 2024
R-4.5-linuxOKNov 10 2024
R-4.4-winOKNov 10 2024
R-4.4-macOKNov 10 2024
R-4.3-winOKNov 10 2024
R-4.3-macOKNov 10 2024

Exports:choicemodelr

Dependencies: