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) "Discrete Choice Methods with Simulation, 2nd Edition" <doi:10.1017/CBO9780511805271>.

Suggests: dplyr, fastDummies, ggplot2, ggrepel, here, kableExtra,

Suggests: apollo, broom, dplyr, fastDummies, ggplot2, ggrepel, gmnl,
gtsummary, here, kableExtra, knitr, mixl, mlogit, rmarkdown,
Imports: generics, MASS, nloptr, parallel, randtoolbox, stats, tibble

Title: Double log normal distribution functions
Packaged: Thu Aug  7 05:11:22 2008; theussl

Description: r,d,p,q functions for the double log normal distribution

Title: Double Log Normal Distribution Functions
Description: Functions to sample from the double log normal distribution and calculate the density, distribution and quantile functions.
Authors@R: c(person("Olaf", "Mersmann", role=c("aut", "cre"), email="olafm@p-value.net"),

Title: Log-multiplicative models, including association models
Description: Functions to fit log-multiplicative models using gnm, with
support for convenient printing, plots, and jackknife/bootstrap
standard errors. Currently supported models include UNIDIFF
(Erikson & Goldthorpe), a.k.a. log-multiplicative layer effect
model (Xie), and several association models: Goodman's
row-column association models of the RC(M) and RC(M)-L families
resp. for two- and three-way tables with one or several
dimensions; two skew-symmetric association models proposed by
Yamaguchi and by van der Heijden & Mooijaart.