bayesdfa
bayesdfa implements Bayesian Dynamic Factor Analysis (DFA) with Stan.
You can install the development version of the package with:
# install.packages("devtools")
devtools::install_github("fate-ewi/bayesdfa")
Funding
The ‘bayesdfa’ package was funded by a NOAA Fisheries and the
Environment (FATE) grant on early warning indicators, led by Mary
Hunsicker and Mike Litzow.
Applications
The ‘bayesdfa’ models were presented to the PFMC’s SSC in November 2017
and have been included in the 2018 California Current Integrated
Ecosystem Report,
https://www.integratedecosystemassessment.noaa.gov/Assets/iea/california/Report/pdf/CCIEA-status-report-2018.pdf
Citation https://journal.r-project.org/archive/2019/RJ-2019-007/index.html
@article{ward_etal_2019,
author = {Eric J. Ward and Sean C. Anderson and Luis A. Damiano and
Mary E. Hunsicker and Michael A. Litzow},
title = {{Modeling regimes with extremes: the bayesdfa package for
identifying and forecasting common trends and anomalies in
multivariate time-series data}},
year = {2019},
journal = {{The R Journal}},
doi = {10.32614/RJ-2019-007},
url = {https://journal.r-project.org/archive/2019/RJ-2019-007/index.html}
}