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ChoiceModelR  

Choice Modeling in R
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("ChoiceModelR", "1.3.1")



Attach the package and use:
library("ChoiceModelR")
Maintained by
John V Colias
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2012-01-04
Latest Update: 2022-05-30
Description:
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.
How to cite:
John V Colias (2012). ChoiceModelR: Choice Modeling in R. R package version 1.3.1, https://cran.r-project.org/web/packages/ChoiceModelR. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0 (2012-01-04 08:34), 1.1 (2012-05-09 06:06), 1.2 (2012-11-21 00:23), 1.3.0 (2022-05-30 08:50)
Other packages that cited ChoiceModelR R package
View ChoiceModelR citation profile
Other R packages that ChoiceModelR depends, imports, suggests or enhances
Complete documentation for ChoiceModelR
Functions, R codes and Examples using the ChoiceModelR R package
Some associated functions: ChoiceModelR-package . choicemodelr . datar . sharedatar . truebetas . 
Some associated R codes: ChoiceModelR.R .  Full ChoiceModelR package functions and examples
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