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bayesdfa  

Bayesian Dynamic Factor Analysis (DFA) with 'Stan'
View on CRAN: Click here


Download and install bayesdfa package within the R console
Install from CRAN:
install.packages("bayesdfa")

Install from Github:
library("remotes")
install_github("cran/bayesdfa")

Install by package version:
library("remotes")
install_version("bayesdfa", "1.3.4")



Attach the package and use:
library("bayesdfa")
Maintained by
Eric J. Ward
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-09-19
Latest Update: 2025-03-22
Description:
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.
How to cite:
Eric J. Ward (2018). bayesdfa: Bayesian Dynamic Factor Analysis (DFA) with 'Stan'. R package version 1.3.4, https://cran.r-project.org/web/packages/bayesdfa. Accessed 04 Jun. 2026.
Previous versions and publish date:
0.1.0 (2018-09-19 12:00), 0.1.1 (2018-11-09 16:30), 0.1.2 (2019-03-05 13:20), 0.1.3 (2019-05-22 15:40), 0.1.5 (2020-09-02 17:50), 0.1.6 (2020-09-21 00:30), 0.1.7 (2021-05-04 19:30), 1.0.0 (2021-05-19 04:00), 1.1.0 (2021-05-28 20:10), 1.2.0 (2021-09-28 15:20), 1.3.1 (2023-10-11 17:10), 1.3.2 (2024-01-12 16:50), 1.3.3 (2024-02-26 21:50)
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Complete documentation for bayesdfa
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