Unobserved Components Models (introduced in Harvey, A. (1989), Forecasting, structural time series models and the Kalman filter, Cambridge New York: Cambridge University Press) decomposes a time series into components such as trend, seasonal, cycle, and the regression effects due to predictor series which captures the salient features of the series to predict its behavior.
# To install from CRAN:
install.packages("rucm")
# Or the development version from GitHub:
# install.packages("devtools")
devtools::install_github("kaushikrch/rucm")
Issues can be reported here.
Package vignette can be found here.
Changes:
- Update
predict.ucm()
to use argumentnewdata
for causal forecasting.
Changes:
- Add a tolerance parameter for the state space model used in
ucm()
Changes:
- Changes in S3 method of printing an UC model. Added p - values for estimates of predictor variables.
- Added a vignette "Unobserved Components Model in R".
- Submitted to CRAN on 2014-09-06.
- First submitted to CRAN on 2014-08-25.