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type: software
title: 'bayesdfa: Bayesian Dynamic Factor Analysis (DFA) with ''Stan'''
version: 1.3.3
doi: 10.32614/CRAN.package.bayesdfa
abstract: Implements Bayesian dynamic factor analysis with 'Stan'. Dynamic factor
  analysis is a dimension reduction tool for multivariate time series. 'bayesdfa'
  extends conventional dynamic factor models in several ways. First, extreme events
  may be estimated in the latent trend by modeling process error with a student-t
  distribution. Second, alternative constraints (including proportions are allowed).
  Third, the estimated dynamic factors can be analyzed with hidden Markov models to
  evaluate support for latent regimes.
authors:
- family-names: Ward
  given-names: Eric J.
  email: eric.ward@noaa.gov
- family-names: Anderson
  given-names: Sean C.
- family-names: Damiano
  given-names: Luis A.
- family-names: Malick
  given-names: Michael J.
- family-names: English
  given-names: Philina A.
repository: https://nmfs-opensci.r-universe.dev
repository-code: https://github.com/fate-ewi/bayesdfa
commit: df97ab8605e9b2ca6883b88f7cee752ef9032121
url: https://fate-ewi.github.io/bayesdfa/
contact:
- family-names: Ward
  given-names: Eric J.
  email: eric.ward@noaa.gov