Imports: caret (>= 6.0-82), dplyr, magrittr, gam, nnet, RcppNumerical,
methods, MASS, graphics, Rcpp (>= 0.12.13)

Author: Jeff Gill <jgill@wustl.edu>, George Casella
<casella@stat.ufl.edu>, Minjung Kyung <kyung@stat.ufl.edu> and
Description: R CODE FOR SIMULATION OF GLMDM

Author: Jeff Gill, George Casella, Minjung Kyung, and Jonathan Rapkin
Description: This package contains functions to perform generalized
linear mixed Dirichlet models using posterior simulation.

Title: Generalized Linear Mixed Effects Models
Authors@R: c(person("Sam Weerahandi", role = "aut"),
person("Mustafa Cavus", role = c("aut", "cre"),
Description: Provides Generalized Inferences based on exact distributions and exact probability statements for mixed effect models, provided by such papers as Weerahandi and Yu (2020) <doi:10.1186/s40488-020-00105-w> under the widely used Compound Symmetric Covariance structure. The package returns the estimation of the coefficients in random and fixed part of the mixed models by generalized inference.
Packaged: 2021-01-21 15:33:28 UTC; mustafacavus

Title: Generalized Linear Mixed Model Trees
Authors@R: c(person(given = "Marjolein", family = "Fokkema", role = c("aut", "cre"), email = "M.Fokkema@fsw.leidenuniv.nl"),
Description: Recursive partitioning based on (generalized) linear mixed models
(GLMMs) combining lmer()/glmer() from lme4 and lmtree()/glmtree() from partykit.
Imports: graphics, stats, utils, Formula

Authors@R: c(person(given = "Marjolein", family = "Fokkema",
role = c("aut", "cre"), email = "M.Fokkema@fsw.leidenuniv.nl"),
person(given = "Achim", family = "Zeileis", role = "aut",
(GLMMs) combining lmer()/glmer() from 'lme4' and lmtree()/glmtree() from
'partykit'.The fitting algorithm is described in more detail in Fokkema,

'partykit'. The fitting algorithm is described in more detail in Fokkema,

Title: GLRT P-Values in Generalized Linear Models
Description: Provides functions to compute Generalized Likelihood Ratio Tests (GLRT) and Rao's score tests of simple
and complex contrasts of Generalized Linear Models (GLMs). It provides the same interface as summary.glm(), adding GLRT P-values,
less biased than Wald's P-values and consistent with profile-likelihood confidence interval generated by confint().
Imports: base, stats, parameters (>= 0.1.0), MASS
Suggests: testthat (>= 2.1.0), lme4, nlme, datasets
Packaged: 2020-03-14 22:01:34 UTC; andre.gillibert