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>.
| Version: | 1.1.593 |
| Depends: | R (≥ 3.6.0) |
| Imports: | brms (≥ 2.21.0), methods,mgcv (≥ 1.8-13),insight (≥0.19.1),marginaleffects (≥ 0.29.0),Rcpp (≥ 0.12.0),rstan (≥ 2.29.0),posterior (≥ 1.0.0),loo (≥ 2.3.1),rstantools (≥ 2.1.1),bayesplot (≥ 1.5.0),ggplot2 (≥ 3.5.0),mvnfast,purrr,dplyr,magrittr,rlang,generics,tibble (≥ 3.0.0),patchwork (≥ 1.2.0) |
| LinkingTo: | Rcpp,RcppArmadillo |
| Suggests: | scoringRules,matrixStats, cmdstanr (≥ 0.5.0),tweedie,splines2,extraDistr,corpcor,wrswoR,ggrepel,ggpp,ggarrow,xts,lubridate,knitr,collapse,rmarkdown,rjags,coda,runjags,usethis,testthat,colorspace |
| Enhances: | gratia (≥ 0.9.0),tidyr |
| Published: | 2025-09-05 |
| DOI: | 10.32614/CRAN.package.mvgam |
| Author: | Nicholas J Clark [aut, cre], KANK Karunarathna [ctb] (ARMA parameterisations and factor models), Sarah Heaps [ctb] (VARMA parameterisations), Scott Pease [ctb] (broom enhancements), Matthijs Hollanders [ctb] (ggplot visualizations) |
| Maintainer: | Nicholas J Clark <nicholas.j.clark1214 at gmail.com> |
| BugReports: | https://github.com/nicholasjclark/mvgam/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/nicholasjclark/mvgam,https://nicholasjclark.github.io/mvgam/ |
| NeedsCompilation: | yes |
| Additional_repositories: | https://mc-stan.org/r-packages/ |
| Citation: | mvgam citation info |
| Materials: | README,NEWS |
| In views: | Bayesian,Environmetrics,TimeSeries |
| CRAN checks: | mvgam results |