ucm: Unobserved components methods for a time series

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

Description

Function ucm decomposes a time series into components such as trend, seasonal, cycle, and the regression effects due to predictor series using Unobserved Components Model (UCM).

Usage

ucm(formula, data, irregular = TRUE, irregular.var = NA, level = TRUE,
  level.var = NA, slope = FALSE, slope.var = NA, season = FALSE,
  season.length = NA, season.var = NA, cycle = FALSE, cycle.period = NA,
  cycle.var = NA, tol = .Machine$double.eps^0.5)

Arguments

formula	an object of class formula containing the symbolic description of the model with dependent and independent terms. If there are no independent terms, replace rhs with 0.
data	a required data frame or list containing variables in the model.
irregular	logical; if irregular component is to be included in the model. Defaults to TRUE.
irregular.var	value to fix variance of irregular component.
level	logical; if level is to be included in the model. Defaults to TRUE.
level.var	value to fix variance of level component.
slope	logical; if slope is to be included in the model along with level. Defaults to FALSE.
slope.var	value to fix variance of the slope component.
season	logical; if seasonal component is to be included in the model. Defaults to FALSE.
season.length	value of length of seasonal component. Required when season is included.
season.var	value to fix variance of seasonal component.
cycle	logical; if cyclical component is to be included in the model. Defaults to FALSE.
cycle.period	length of cyclical component. Required when cycle is included.
cycle.var	value to fix variance of cyclical component.
tol	Used by KFAS::SSModel. A tolerance parameter used in checking whether Finf or F is numerically zero. Defaults to .Machine$double.eps^0.5. If smoothing gives negative variances for smoothed states, try adjusting this.

Details

Formula of the model can be of the forma as in lm with response variable on rhs and predictor variables or 0 (if no predictor variables) on the rhs.

Value

object of class ucm, which is a list with the following components:

est	Estimates of predictor variables, if present.
irr.var	Estimated variance of irregular component, if present.
est.var.level	Estimated variance of the level component, if present.
est.var.slope	Estimated variance of slope of the level, if present.
est.var.season	Estimated variance of the seasonal component, if present.
est.var.cycle	Estimated variance of the cyclical component, if present.
s.level	An object of the same class as of dependent variable containing the time varying level values, if level is present.
s.lope	An object of the same class as of dependent variable containing the time varying slope values, if slope is present.
s.season	An object of the same class as of dependent variable containing the time varying seasonal values, if season is present.
s.cycle	An object of the same class as of dependent variable containing the time varying cyclical values, if cycle is present.
vs.level	A vector containing time varying estimated variance of level, if level is present.
vs.slope	A vector containing time varying estimated variance of slope, if slope is present.
vs.season	A vector containing time varying estimated variance of seasonal component, if season is present.
vs.cycle	A vector containing time varying estimated variance of cyclical component, if cycle is present.
call	Original call of the function.
model	The original model of class SSModel from KFAS package.

See Also

KFAS, SSModel for a detailed discussion on State Space Models.

Examples

modelNile <- ucm(Nile~0, data = Nile, slope = TRUE)
modelNile
modelNile$s.level

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