Package: gRim 0.3.4

Søren Højsgaard

gRim: Graphical Interaction Models

Provides the following types of models: Models for contingency tables (i.e. log-linear models) Graphical Gaussian models for multivariate normal data (i.e. covariance selection models) Mixed interaction models. Documentation about 'gRim' is provided by vignettes included in this package and the book by Højsgaard, Edwards and Lauritzen (2012, <doi:10.1007/978-1-4614-2299-0>); see 'citation("gRim")' for details.

Authors:Søren Højsgaard [aut, cre]

gRim_0.3.4.tar.gz
gRim_0.3.4.tar.gz(r-4.5-noble)gRim_0.3.4.tar.gz(r-4.4-noble)
gRim_0.3.4.tgz(r-4.4-emscripten)gRim_0.3.4.tgz(r-4.3-emscripten)
gRim.pdf |gRim.html
gRim/json (API)
NEWS

# Install 'gRim' in R:
install.packages('gRim', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

4.46 score 2 stars 72 scripts 987 downloads 70 exports 50 dependencies

Last updated 2 months agofrom:2bf58b389e. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-linux-x86_64OKNov 15 2024

Exports:as_amat2ematas_elist2ematas_emat_complementas_emat2amatas_emat2cqas_emat2elistas_emat2glistas_emat2graphas_emat2igraphas_glist2cqas_glist2ematas_glist2graphas_glist2igraphas_glist2out_edgesas_K2amatas_K2graphas_sparsebackwardCGstatsciTestciTest_dfciTest_mvnciTest_ordinalcmodconcentrationdim_loglindim_loglin_decompdmodeffloglinemat_compareemat_complementemat_sortextract_cmod_datafast_covfit_ggm_gripsforwardgenerate_n01getEdgesgetInEdgesgetmigetOutEdgesggmfitggmfitrglance.gips_fit_classimpose_zerommodmodel_linemodel_loopmodel_randommodel_random_treemodel_rectangular_gridmodel_saturatedmodel_starmodify_glistorder_rowsparm_CGstats2mmodparm_ghk2phkparm_ghk2pmsparm_moment2pmsparm_phk2ghkparm_phk2pmsparm_pms2ghkparm_pms2phkparse_gm_formulaplottestaddtestdeletetestEdgestestInEdgestestOutEdges

Dependencies:backportsbootbroomclicolorspacecowplotcpp11DerivdoBydplyrfansifarvergenericsggplot2gluegRaingRbasegtableigraphisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmicrobenchmarkmodelrmunsellnlmepillarpkgconfigpurrrR6RColorBrewerRcppRcppArmadilloRcppEigenrlangscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

Graphical Interaction Models

Rendered fromgrim.rmdusingknitr::knitron Nov 15 2024.

Last update: 2024-07-20
Started: 2024-07-20

Readme and manuals

Help Manual

Help pageTopics
Mean, covariance and counts for grouped data (statistics for conditional Gaussian distribution).cg-stats CGstats CGstats.data.frame
Test for conditional independence in a contingency tablecitest-array ciTest_table
Test for conditional independence in a dataframecitest-df ciTest_df
Generic function for conditional independence testciTest citest-generic
Test for conditional independence in the multivariate normal distributioncitest-mvn ciTest_mvn
A function to compute Monte Carlo and asymptotic tests of conditional independence for ordinal and/or nominal variables.citest-ordinal ciTest_ordinal
Graphical Gaussian modelcmod extract_cmod_data
Coerce models to different representationsas_amat2emat as_elist2emat as_emat2amat as_emat2cq as_emat2elist as_emat2glist as_emat2graph as_emat2igraph as_emat_complement as_glist2cq as_glist2emat as_glist2graph as_glist2igraph as_glist2out_edges as_K2amat as_K2graph as_sparse coerce_models
Edge matrix operationsemat_compare emat_complement emat_operations emat_sort order_rows
Fast computation of covariance / correlation matrixfast_cov
Fit Gaussian graphical modelsfit_ggm_grips
Generate various grapical modelsemat_saturated_model generate_models model_line model_loop model_random model_random_tree model_rectangular_grid model_saturated model_star
Genrate matrix of N(0, 1) variablesgenerate_n01
Find edges in a graph or edges not in an undirected graph.getEdges getEdges.graphNEL getEdges.list getEdges.matrix getEdgesMAT getInEdges getInEdgesMAT getOutEdges getOutEdgesMAT
Iterative proportional fitting of graphical Gaussian modelggmfit ggmfitr
Discrete interaction model (log-linear model)dmod fitted.dModel imodel-dmod print.dModel residuals.dModel
General functions related to iModelsextractAIC.iModel formula.iModel imodel-general isDecomposable.dModel isGraphical.dModel logLik.iModel modelProperties modelProperties.dModel print.iModelsummary summary.iModel terms.iModel
Get information about mixed interaction model objectsgetmi imodel-info
Mixed interaction model.coef.mModel coefficients.mModel imodel-mmod mmod mmod_dimension print.mModel summary.mModel
Impose zeros in matrix entries which do not correspond to an edge.impose_zero
Internal functions for the gRim package%>% internal
Return the dimension of a log-linear modeldim_loglin dim_loglin_decomp loglin-dim
Fitting Log-Linear Models by Message Passingeffloglin loglin-effloglin
Modify generating class for a graphical/hierarchical modelmodify_glist
Conversion between different parametrizations of mixed modelsparm-conversion parm_CGstats2mmod parm_ghk2phk parm_ghk2pms parm_moment2pms parm_phk2ghk parm_phk2pms parm_pms2ghk parm_pms2phk
Parse graphical model formulaparse_gm_formula
Stepwise model selection in (graphical) interaction modelsbackward drop_func forward stepwise stepwise.iModel
Test edges in graphical models with p-value/AIC valuetest-edges testEdges testInEdges testOutEdges
Test addition of edge to graphical modelprint.testadd testadd testadd.iModel testadd.mModel
Test deletion of edge from an interaction modelprint.testdelete testdelete testdelete.iModel testdelete.mModel
Utilities for gRipsAIC.gips_fit_class BIC.gips_fit_class concentration concentration.gips_fit_class glance.gips_fit_class logLik.gips_fit_class print.gips_fit_class sigma.gips_fit_class summary.gips_fit_class utilities_grips