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, autoregressive and moving average components can be optionally included. Third, the estimated dynamic factors can be analyzed with hidden Markov models to evaluate support for latent regimes.

Package details

AuthorEric J. Ward [aut, cre], Sean C. Anderson [aut], Luis A. Damiano [aut], Mary E. Hunsicker, [ctb], Mike A. Litzow [ctb], Trustees of Columbia University [cph]
MaintainerEric J. Ward <[email protected]>
LicenseGPL (>= 3)
Version0.1.3
URL https://github.com/fate-ewi/bayesdfa
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("bayesdfa")

Try the bayesdfa package in your browser

Any scripts or data that you put into this service are public.

bayesdfa documentation built on May 22, 2019, 5:02 p.m.