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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 studentt 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.
Package details 


Author  Eric J. Ward [aut, cre], Sean C. Anderson [aut], Luis A. Damiano [aut], Michael J. Malick [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] 
Maintainer  Eric J. Ward <eric.ward@noaa.gov> 
License  GPL (>= 3) 
Version  1.1.0 
URL  https://fateewi.github.io/bayesdfa/ 
Package repository  View on CRAN 
Installation 
Install the latest version of this package by entering the following in R:

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