This package is considered a duplicate. The official version of this package is found at:https://fate-ewi.r-universe.dev/bayesdfa

Package: bayesdfa 1.3.5

Eric J. Ward

bayesdfa: Bayesian Dynamic Factor Analysis (DFA) with 'Stan'

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:Eric J. Ward [aut, cre], Sean C. Anderson [aut], Luis A. Damiano [aut], Michael J. Malick [aut], Philina A. English [aut], Mary E. Hunsicker, [ctb], Mike A. Litzow [ctb], Mark D. Scheuerell [ctb], Elizabeth E. Holmes [ctb], Nick Tolimieri [ctb], Trustees of Columbia University [cph]

bayesdfa_1.3.5.tar.gz
bayesdfa_1.3.5.zip(r-4.7)bayesdfa_1.3.5.zip(r-4.6)bayesdfa_1.3.5.zip(r-4.5)
bayesdfa_1.3.5.tgz(r-4.6-x86_64)bayesdfa_1.3.5.tgz(r-4.6-arm64)bayesdfa_1.3.5.tgz(r-4.5-x86_64)bayesdfa_1.3.5.tgz(r-4.5-arm64)
bayesdfa_1.3.5.tar.gz(r-4.7-arm64)bayesdfa_1.3.5.tar.gz(r-4.7-x86_64)bayesdfa_1.3.5.tar.gz(r-4.6-arm64)bayesdfa_1.3.5.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bayesdfa/json (API)

# Install 'bayesdfa' in R:

install.packages('bayesdfa', repos = c('https://atsa-es.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/fate-ewi/bayesdfa/issues

Pkgdown/docs site:https://fate-ewi.github.io

Uses libs:

c++– GNU Standard C++ Library v3

On CRAN:

cpp

7.94 score 29 stars 103 scripts 1.0k downloads 21 exports 56 dependencies

Last updated from:4687b27746. Checks:12 OK, 1 FAIL. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	500
linux-devel-x86_64	OK	501
source / vignettes	OK	729
linux-release-arm64	OK	477
linux-release-x86_64	OK	482
macos-release-arm64	OK	296
macos-release-x86_64	OK	798
macos-oldrel-arm64	OK	334
macos-oldrel-x86_64	OK	751
windows-devel	OK	682
windows-release	OK	567
windows-oldrel	OK	592
wasm-release	FAIL	159

Exports:dfa_cv dfa_fitted dfa_loadings dfa_trends find_dfa_trends find_inverted_chains find_regimes find_swans fit_dfa fit_regimes invert_chains is_converged loo plot_fitted plot_loadings plot_regime_model plot_trends predicted rotate_trends sim_dfa trend_cor

Dependencies:abind backports BH callr checkmate cli cpp11 desc distributional dplyr farver generics ggplot2 glue gridExtra gtable inline isoband labeling lattice lifecycle loo magrittr Matrix matrixStats mgcv nlme numDeriv pillar pkgbuild pkgconfig plyr posterior processx ps QuickJSR R6 RColorBrewer Rcpp RcppEigen RcppParallel reshape2 rlang rstan S7 scales StanHeaders stringi stringr tensorA tibble tidyselect utf8 vctrs viridisLite withr

Overview of the bayesdfa package

Rendered froma1_bayesdfa.Rmdusingknitr::rmarkdown

Last update: 2023-12-07
Started: 2023-04-20

Combining data with bayesdfa

Example

Rendered froma2_combining_data.Rmdusingknitr::rmarkdown

Last update: 2023-04-24
Started: 2023-04-20

Estimating process trend variability with bayesdfa

Case 1: unequal trend variability | Candidate models | Recovering loadings | Recovering trends | Summary

Rendered froma5_estimate_process_sigma.Rmdusingknitr::rmarkdown