glmmsr: Fit a Generalized Linear Mixed Model

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Conduct inference about generalized linear mixed models, with a choice about which method to use to approximate the likelihood. In addition to the Laplace and adaptive Gaussian quadrature approximations, which are borrowed from 'lme4', the likelihood may be approximated by the sequential reduction approximation, or an importance sampling approximation. These methods provide an accurate approximation to the likelihood in some situations where it is not possible to use adaptive Gaussian quadrature.

Author
Helen Ogden [aut, cre]
Date of publication
2016-03-13 11:29:42
Maintainer
Helen Ogden <heogden12@gmail.com>
License
GPL (>= 2)
Version
0.1.1
URLs

View on CRAN

Man pages

calibration_parameters
Parameters needed to calibrate the cluster tree
cluster_graph
The beliefs for the clusters and sepsets of a cluster tree,...
continuous_beliefs
A vector of terms in the factorization of a graphical model,...
find_approximation_name
Find the name of the likelihood approximation used for...
find_lfun_glmm
Find the log-likelihood function
find_modfr_glmm
Parse a formula (and possibly subformulas)
glmm
Fit a GLMM
glmmFit
Construct a glmmFit object
glmmsr
glmmsr: fit GLMMs with various approximation methods
optimize_glmm
Maximize the approximated log-likelihood
print.glmmFit
Print glmmFit object
print.summaryGlmmFit
Print summaryGlmmFit object
summary.glmmFit
Summarize a glmmFit object
summaryGlmmFit
Construct a summaryGlmmFit object
three_level
A dataset simulated from a three-level model
two_level
A dataset simulated from a two-level model

Files in this package

glmmsr
glmmsr/inst
glmmsr/inst/continuous_beliefs.yml
glmmsr/inst/examples
glmmsr/inst/examples/chameleons.R
glmmsr/inst/examples/three_level.R
glmmsr/inst/examples/two_level.R
glmmsr/inst/RcppR6.yml
glmmsr/inst/cluster_graph.yml
glmmsr/inst/doc
glmmsr/inst/doc/glmmsr-vignette.pdf
glmmsr/inst/doc/glmmsr-vignette.Rmd
glmmsr/inst/doc/glmmsr-vignette.R
glmmsr/inst/calibration_parameters.yml
glmmsr/inst/include
glmmsr/inst/include/testingEigen.h
glmmsr/inst/include/NormalBelief.h
glmmsr/inst/include/Quadratic.h
glmmsr/inst/include/BeliefBase.h
glmmsr/inst/include/Basis.h
glmmsr/inst/include/ContinuousBeliefBase.h
glmmsr/inst/include/matrixHelper.h
glmmsr/inst/include/Point.h
glmmsr/inst/include/Family.h
glmmsr/inst/include/ProbitLink.h
glmmsr/inst/include/glmmsr.h
glmmsr/inst/include/LogitLink.h
glmmsr/inst/include/subsetEigen.h
glmmsr/inst/include/accessParameters.h
glmmsr/inst/include/BasisLevel.h
glmmsr/inst/include/ContinuousBelief.h
glmmsr/inst/include/adjacency_list_alt.h
glmmsr/inst/include/CoversBelief.h
glmmsr/inst/include/MixedContinuousBeliefVector.h
glmmsr/inst/include/SparseStore.h
glmmsr/inst/include/counting.h
glmmsr/inst/include/Parameters.h
glmmsr/inst/include/SparseGridTransform.h
glmmsr/inst/include/dependenceGraph.h
glmmsr/inst/include/QuadratureRule.h
glmmsr/inst/include/Binomial.h
glmmsr/inst/include/itemsHelper.h
glmmsr/inst/include/SparseGrid.h
glmmsr/inst/include/FamilyGivenMean.h
glmmsr/inst/include/Graph.h
glmmsr/inst/include/SparseBelief.h
glmmsr/inst/include/IntegratedFunction.h
glmmsr/inst/include/ClusterGraph.h
glmmsr/inst/include/GLMMBelief.h
glmmsr/inst/include/LinkBase.h
glmmsr/inst/include/FamilyBase.h
glmmsr/inst/include/glmmsr
glmmsr/inst/include/glmmsr/RcppR6_pre.hpp
glmmsr/inst/include/glmmsr/RcppR6_support.hpp
glmmsr/inst/include/glmmsr/RcppR6_post.hpp
glmmsr/inst/include/Link.h
glmmsr/inst/include/MixedContinuousBelief.h
glmmsr/inst/include/MultiNormal.h
glmmsr/tests
glmmsr/tests/testthat.R
glmmsr/tests/testthat
glmmsr/tests/testthat/test_utility.R
glmmsr/tests/testthat/test_loglikelihood.R
glmmsr/tests/testthat/pdg_three_level.rds
glmmsr/tests/testthat/test_subformula.R
glmmsr/tests/testthat/test_modify_subexpr.R
glmmsr/tests/testthat/subs_ability_stuff.rds
glmmsr/tests/testthat/test_indexing.R
glmmsr/tests/testthat/pdg_two_level.rds
glmmsr/tests/testthat/test_fit.R
glmmsr/tests/testthat/test_model_frames.R
glmmsr/src
glmmsr/src/MixedContinuousBelief.cpp
glmmsr/src/Makevars
glmmsr/src/ContinuousBeliefBase.cpp
glmmsr/src/NormalBelief.cpp
glmmsr/src/BeliefBase.cpp
glmmsr/src/LinkBase.cpp
glmmsr/src/MixedContinuousBeliefVector.cpp
glmmsr/src/Quadratic.cpp
glmmsr/src/RcppR6.cpp
glmmsr/src/Link.cpp
glmmsr/src/Graph.cpp
glmmsr/src/MultiNormal.cpp
glmmsr/src/Binomial.cpp
glmmsr/src/ClusterGraph.cpp
glmmsr/src/FamilyBase.cpp
glmmsr/src/SparseStore.cpp
glmmsr/src/FamilyGivenMean.cpp
glmmsr/src/SparseGridTransform.cpp
glmmsr/src/counting.cpp
glmmsr/src/SparseGrid.cpp
glmmsr/src/IntegratedFunction.cpp
glmmsr/src/accessParameters.cpp
glmmsr/src/matrixHelper.cpp
glmmsr/src/BasisLevel.cpp
glmmsr/src/Parameters.cpp
glmmsr/src/Point.cpp
glmmsr/src/ProbitLink.cpp
glmmsr/src/ContinuousBelief.cpp
glmmsr/src/Basis.cpp
glmmsr/src/SparseBelief.cpp
glmmsr/src/itemsHelper.cpp
glmmsr/src/QuadratureRule.cpp
glmmsr/src/RcppExports.cpp
glmmsr/src/Family.cpp
glmmsr/src/GLMMBelief.cpp
glmmsr/src/LogitLink.cpp
glmmsr/src/subsetEigen.cpp
glmmsr/NAMESPACE
glmmsr/data
glmmsr/data/two_level.rda
glmmsr/data/three_level.rda
glmmsr/R
glmmsr/R/loglikelihood.R
glmmsr/R/IS.R
glmmsr/R/modify_subexpr.R
glmmsr/R/indexing.R
glmmsr/R/glmmFit.R
glmmsr/R/control.R
glmmsr/R/RcppR6.R
glmmsr/R/utility.R
glmmsr/R/fit.R
glmmsr/R/RcppExports.R
glmmsr/R/optimization.R
glmmsr/R/glmmsr.R
glmmsr/R/splitframe.R
glmmsr/R/subformula.R
glmmsr/R/model_frames.R
glmmsr/vignettes
glmmsr/vignettes/glmmsr.bib
glmmsr/vignettes/glmmsr-vignette.Rmd
glmmsr/README.md
glmmsr/MD5
glmmsr/build
glmmsr/build/vignette.rds
glmmsr/DESCRIPTION
glmmsr/man
glmmsr/man/print.summaryGlmmFit.Rd
glmmsr/man/glmmsr.Rd
glmmsr/man/find_lfun_glmm.Rd
glmmsr/man/glmmFit.Rd
glmmsr/man/glmm.Rd
glmmsr/man/find_approximation_name.Rd
glmmsr/man/find_modfr_glmm.Rd
glmmsr/man/print.glmmFit.Rd
glmmsr/man/summary.glmmFit.Rd
glmmsr/man/two_level.Rd
glmmsr/man/three_level.Rd
glmmsr/man/cluster_graph.Rd
glmmsr/man/summaryGlmmFit.Rd
glmmsr/man/optimize_glmm.Rd
glmmsr/man/continuous_beliefs.Rd
glmmsr/man/calibration_parameters.Rd