mvgam: Multivariate (Dynamic) Generalized Additive Models

Fit Bayesian Dynamic Generalized Additive Models to sets of time series. Users can build dynamic 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 (2022) <doi:10.1111/2041-210X.13974>.

Package details

AuthorNicholas J Clark [aut, cre] (<https://orcid.org/0000-0001-7131-3301>)
MaintainerNicholas J Clark <nicholas.j.clark1214@gmail.com>
LicenseMIT + file LICENSE
Version1.1.2
URL https://github.com/nicholasjclark/mvgam https://nicholasjclark.github.io/mvgam/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("mvgam")

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mvgam documentation built on July 1, 2024, 9:07 a.m.