Acknowledgments: Ideas and input provided by R. Harald Baayen as well
as Terrance M. Nearey in the development of the polytomous
Poisson reformulation function allowing for mixed-effects
logistic regression modeling of polytomous outcome settings are

Description: Logistic regression modeling for polytomous settings (more than two categorical outcomes) with both fixed and mixed effect predictors, and univariate and bivariate analysis of categorical, unordered data.
Acknowledgements: Ideas and input provided by R. Harald Baayen as well

Title: Bootstrapped Basis Regression with Oracle Model Selection
Author: Brenton Kenkel and Curtis S. Signorino
Description: Routines for flexible functional form estimation via basis
regression, with model selection via the adaptive LASSO or SCAD
Depends: glmnet (>= 1.5.1), ncvreg, Formula, Matrix
Collate: 'helpers.r' 'fn_pred.r' 'fn_plot.r' 'fn_poly.r' 'polywog.r'

Depends: glmnet (>= 1.5.1), ncvreg, Formula, Matrix, miscTools
Imports: stringr, games, car, matrixStats
Collate: 'helpers.r' 'fn_pred.r' 'fn_plot.r' 'fn_poly.r' 'fitters.r'

regression, with model selection via the adaptive LASSO or SCAD to prevent
Imports: foreach, Formula, glmnet (>= 1.9-5), iterators, Matrix, ncvreg

Author: Fawn Hornsby, Ryan Nielson, and Trent McDonald
Description: This package fits a patch occupancy model

Title: Graphical Check for Proportional Odds Assumption
Description: Implements the method described at the UCLA Statistical
for checking if the proportional odds assumption holds for a
Imports: dplyr, tidyr, ggplot2, assertthat, stats, rlang, magrittr,
Author: Melissa Wong [aut, cre] (<https://orcid.org/0000-0002-2973-6279>)

Imports: dplyr, tidyr (>= 1.0.0), ggplot2, assertthat, stats, rlang,

Title: Solver for Partially Observable Markov Decision Processes
Authors@R: c(person("Hossein", "Kamalzadeh", email = "hkamalzadeh@smu.edu",
person("Michael", "Hahsler", email = "mhahsler@lyle.smu.edu",
Description: Provides an interface to pomdp-solve, a solver for Partially Observable Markov Decision Processes (POMDP). The package enables the user to simply define all components of a POMDP model and solve the problem using several methods. The package also contains functions to analyze and visualize the POMDP solutions (e.g., the optimal policy).
Copyright: pomdp-solve is Copyright (C) Anthony R. Cassandra; LASPack
is Copyright (C) Tomas Skalicky; lp-solve is Copyright (C)
Michel Berkelaar, Kjell Eikland, Peter Notebaert; all other
code is Copyright (C) Hossein Kamalzadeh and Michael Hahsler.
Author: Hossein Kamalzadeh [aut, cph, cre],