ucm: Unobserved components methods for a time series
In rucm: Implementation of Unobserved Components Model (UCM)

Description Usage Arguments Details Value See Also Examples

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).

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)

`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.

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.

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.

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

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

Loading required package: KFAS
Call:
ucm(formula = Nile ~ 0, data = Nile, slope = TRUE)

Parameter estimates:
NULL

Estimated variance:
Irregular_Variance     Level_Variance     Slope_Variance 
        14706.3488          1742.8776             0.0037 
Time Series:
Start = 1871 
End = 1970 
Frequency = 1 
  [1] 1120.8009 1117.4788 1109.1175 1118.0728 1116.1336 1108.9957 1095.8132
  [8] 1116.1474 1122.9887 1100.5562 1073.4490 1055.6391 1052.1264 1041.7550
 [15] 1037.0432 1034.3513 1040.4710 1030.0549 1047.0217 1074.5386 1094.2975
 [22] 1113.3805 1121.0129 1125.2097 1114.6172 1086.7950 1043.1863 1001.1402
 [29]  947.3782  914.1638  889.7388  867.1794  865.1441  854.2378  845.8487
 [36]  854.6263  856.1307  877.0868  881.1062  865.1100  836.8018  809.1814
 [43]  791.4195  813.4091  834.1440  870.5398  877.3717  857.8198  841.3280
 [50]  834.0008  828.2145  829.5646  829.0858  824.4694  815.4054  820.2556
 [57]  822.1736  833.3563  848.9664  841.9368  844.7365  855.0898  864.2687
 [64]  875.7314  879.1034  870.0440  857.7901  849.7778  822.7773  801.9132
 [71]  795.9715  807.4479  814.3556  821.5425  838.1563  859.1736  858.7608
 [78]  858.2011  855.7691  854.2579  848.5107  855.1494  874.3680  897.8965
 [85]  903.3988  907.1706  901.6000  908.4256  913.5237  911.3360  920.5651
 [92]  918.0096  916.8773  917.6264  888.4659  856.5162  837.6638  809.1721
 [99]  791.4852  782.9813