Package: gRim 0.3.3
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:
gRim_0.3.3.tar.gz
gRim_0.3.3.tar.gz(r-4.5-noble)gRim_0.3.3.tar.gz(r-4.4-noble)
gRim_0.3.3.tgz(r-4.4-emscripten)gRim_0.3.3.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')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 months agofrom:6ef7912e8d. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 19 2024 |
| R-4.5-linux-x86_64 | NOTE | Aug 19 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
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| 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 table | citest-array ciTest_table |
| Test for conditional independence in a dataframe | citest-df ciTest_df |
| Generic function for conditional independence test | ciTest citest-generic |
| Test for conditional independence in the multivariate normal distribution | citest-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 model | cmod extract_cmod_data |
| Coerce models to different representations | as_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 operations | emat_compare emat_complement emat_operations emat_sort order_rows |
| Fast computation of covariance / correlation matrix | fast_cov |
| Fit Gaussian graphical models | fit_ggm_grips |
| Generate various grapical models | emat_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) variables | generate_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 model | ggmfit ggmfitr |
| Discrete interaction model (log-linear model) | dmod fitted.dModel imodel-dmod print.dModel residuals.dModel |
| General functions related to iModels | extractAIC.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 objects | getmi 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 model | dim_loglin dim_loglin_decomp loglin-dim |
| Fitting Log-Linear Models by Message Passing | effloglin loglin-effloglin |
| Modify generating class for a graphical/hierarchical model | modify_glist |
| Conversion between different parametrizations of mixed models | parm-conversion parm_CGstats2mmod parm_ghk2phk parm_ghk2pms parm_moment2pms parm_phk2ghk parm_phk2pms parm_pms2ghk parm_pms2phk |
| Parse graphical model formula | parse_gm_formula |
| Stepwise model selection in (graphical) interaction models | backward drop_func forward stepwise stepwise.iModel |
| Test edges in graphical models with p-value/AIC value | test-edges testEdges testInEdges testOutEdges |
| Test addition of edge to graphical model | print.testadd testadd testadd.iModel testadd.mModel |
| Test deletion of edge from an interaction model | print.testdelete testdelete testdelete.iModel testdelete.mModel |
| Utilities for gRips | AIC.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 |
