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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: 709ed7aaf096ea82dd00b3cc0dfd3cd241f57886
url: https://fate-ewi.github.io/bayesdfa/
contact:
- family-names: Ward
  given-names: Eric J.
  email: eric.ward@noaa.gov