README.md

In kaushikrch/rucm: Implementation of Unobserved Components Model (UCM) in R

rucm

Implementation of Unobserved Components Models (UCM) in R

Description

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.

Installation

# 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.

Vignette

Package vignette can be found here.

Package News

rucm v0.6.2

Changes:

• Update predict.ucm() to use argument newdata for causal forecasting.

rucm v0.6.1

Changes:

• Add a tolerance parameter for the state space model used in ucm()

rucm v0.4

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.

rucm v0.3

• First submitted to CRAN on 2014-08-25.

kaushikrch/rucm documentation built on May 18, 2019, 5:50 a.m.