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bayesdfa
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]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.bayesdfa . https://github.com/fate-ewi/bayesdfa/issues . https://fate-ewi.github.io/bayesdfa/ . bayesdfa results . bayesdfa.pdf . Overview of the bayesdfa package . Combining data with bayesdfa . Examples of including covariates with bayesdfa . Estimating process trend variability with bayesdfa . Fitting compositional dynamic factor models with bayesdfa . bayesdfa_1.3.4.tar.gz . bayesdfa_1.3.4.zip . bayesdfa_1.3.4.zip . bayesdfa_1.3.4.zip . bayesdfa_1.3.4.tgz . bayesdfa_1.3.4.tgz . bayesdfa_1.3.4.tgz . bayesdfa_1.3.4.tgz . bayesdfa archive . https://CRAN.R-project.org/package=bayesdfa .
First Published: 2018-09-19
Latest Update: 2024-02-26
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 05 May. 2025.
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)
Other packages that cited bayesdfa R package
View bayesdfa citation profile
Other R packages that bayesdfa depends,
imports, suggests or enhances
Complete documentation for bayesdfa
Functions, R codes and Examples using
the bayesdfa R package
Some associated functions: bayesdfa-package . dfa_cv . dfa_fitted . dfa_loadings . dfa_trends . find_dfa_trends . find_inverted_chains . find_regimes . find_swans . fit_dfa . fit_regimes . hmm_init . invert_chains . is_converged . loo . plot_fitted . plot_loadings . plot_regime_model . plot_trends . predicted . rotate_trends . sim_dfa . trend_cor .
Some associated R codes: bayesdfa-package.R . converge_rhat.R . dfa_cv.R . dfa_fitted.R . dfa_loadings.R . dfa_trends.R . find_dfa_trends.R . find_regimes.R . find_swans.R . fit_dfa.R . fit_regimes.R . hmm_init.R . invert_chains.R . loo.R . plot_fitted.R . plot_loadings.R . plot_regime_model.R . plot_trends.R . predicted.R . print.R . rotate_trends.R . sim.R . stanmodels.R . trend_cor.R . Full bayesdfa package functions and examples
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