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}
}