Package: mvgam 1.1.595

mvgam: Multivariate (Dynamic) Generalized Additive Models
Fit Bayesian Dynamic Generalized Additive Models to multivariate observations. Users can build nonlinear State-Space models that can incorporate semiparametric effects in observation and process components, using a wide range of observation families. Estimation is performed using Markov Chain Monte Carlo with Hamiltonian Monte Carlo in the software 'Stan'. References: Clark & Wells (2023) <doi:10.1111/2041-210X.13974>.
Authors:
mvgam_1.1.595.tar.gz
mvgam_1.1.595.zip(r-4.7)mvgam_1.1.595.zip(r-4.6)mvgam_1.1.595.zip(r-4.5)
mvgam_1.1.595.tgz(r-4.6-x86_64)mvgam_1.1.595.tgz(r-4.6-arm64)mvgam_1.1.595.tgz(r-4.5-x86_64)mvgam_1.1.595.tgz(r-4.5-arm64)
mvgam_1.1.595.tar.gz(r-4.7-arm64)mvgam_1.1.595.tar.gz(r-4.7-x86_64)mvgam_1.1.595.tar.gz(r-4.6-arm64)mvgam_1.1.595.tar.gz(r-4.6-x86_64)
mvgam_1.1.595.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
mvgam/json (API)
NEWS
| # Install 'mvgam' in R: |
| install.packages('mvgam', repos = c('https://nicholasjclark.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/nicholasjclark/mvgam/issues
Pkgdown/docs site:https://nicholasjclark.github.io
- all_neon_tick_data - NEON Amblyomma and Ixodes tick abundance survey data
- portal_data - Portal Project rodent capture survey data
bayesian-statisticsdynamic-factor-modelsecological-modellingforecastinggaussian-processgeneralised-additive-modelsgeneralized-additive-modelsjoint-species-distribution-modellingmultilevel-modelsmultivariate-timeseriesstantime-series-analysistimeseriesvector-autoregressionvectorautoregressionopenblascpp
Last updated from:c8617ef108. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 327 | ||
| linux-devel-x86_64 | OK | 360 | ||
| source / vignettes | OK | 437 | ||
| linux-release-arm64 | OK | 358 | ||
| linux-release-x86_64 | OK | 305 | ||
| macos-release-arm64 | OK | 240 | ||
| macos-release-x86_64 | OK | 736 | ||
| macos-oldrel-arm64 | OK | 236 | ||
| macos-oldrel-x86_64 | OK | 602 | ||
| windows-devel | OK | 488 | ||
| windows-release | OK | 343 | ||
| windows-oldrel | OK | 422 | ||
| wasm-release | OK | 203 |
Exports:%>%add_residualsARas_drawsas_draws_arrayas_draws_dfas_draws_listas_draws_matrixas_draws_rvarsaugmentavg_predictionsbernoullibeta_binomialbetarCARcodecompare_mvgamscomparisonsconditional_effectsdatagriddrawDotmvgamdynamicensembleeval_mvgameval_smoothDothilbertDotsmootheval_smoothDotmodDotsmootheval_smoothDotmoiDotsmoothfevdforecastget_dataget_mvgam_priorsget_predictgpGPhindcasthow_to_citehypothesesirfjsdgamlfo_cvlognormallooloo_comparelv_correlationsmcmc_plotmvgamnbneff_rationmixnuts_paramsordinateplot_comparisonsplot_mvgam_factorsplot_mvgam_fcplot_mvgam_ptermsplot_mvgam_randomeffectsplot_mvgam_residsplot_mvgam_seriesplot_mvgam_smoothplot_mvgam_trendplot_mvgam_uncertaintyplot_predictionsplot_slopesposterior_epredposterior_linpredposterior_predictpp_checkppcpredictionspriorprior_prior_stringPWresidual_corrhatroll_eval_mvgamRWsscoreseries_to_mvgamset_priorsim_mvgamslopesstabilitystancodestandatastudentstudent_tt2tetitidytweedieVARvariablesZMVN
Dependencies:abindbackportsbayesplotBHbridgesamplingbrmsBrobdingnagcallrcheckmateclicodacodetoolscpp11data.tabledescdigestdistributionaldplyrfarverFormulafuturefuture.applygenericsggplot2ggridgesglobalsgluegridExtragtableinlineinsightisobandlabelinglatticelifecyclelistenvloomagrittrmarginaleffectsMatrixmatrixStatsmgcvmvnfastmvtnormnleqslvnlmenumDerivparallellypatchworkpillarpkgbuildpkgconfigplyrposteriorprocessxpspurrrQuickJSRR6RColorBrewerRcppRcppArmadilloRcppEigenRcppParallelreshape2rlangrstanrstantoolsS7scalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr
Forecasting and forecast evaluation in mvgam
Rendered fromforecast_evaluation.Rmdusingknitr::rmarkdownon May 14 2026.Last update: 2025-03-14
Started: 2023-10-23
Formatting data for use in mvgam
Rendered fromdata_in_mvgam.Rmdusingknitr::rmarkdownon May 14 2026.Last update: 2025-09-04
Started: 2023-09-20
N-mixtures in mvgam
Rendered fromnmixtures.Rmdusingknitr::rmarkdownon May 14 2026.Last update: 2025-02-27
Started: 2024-01-29
Overview of the mvgam package
Rendered frommvgam_overview.Rmdusingknitr::rmarkdownon May 14 2026.Last update: 2025-05-08
Started: 2023-08-29
Shared latent states in mvgam
Rendered fromshared_states.Rmdusingknitr::rmarkdownon May 14 2026.Last update: 2026-01-19
Started: 2023-09-29
State-Space models in mvgam
Rendered fromtrend_formulas.Rmdusingknitr::rmarkdownon May 14 2026.Last update: 2026-01-19
Started: 2023-09-01
Time-varying effects in mvgam
Rendered fromtime_varying_effects.Rmdusingknitr::rmarkdownon May 14 2026.Last update: 2026-01-19
Started: 2023-10-14
