UComp (version 2.1)

UCmodel: UCmodel

Description

Estimates and forecasts UC general univariate models

Usage

UCmodel(
  y,
  u = NULL,
  model = "?/none/?/?",
  h = NA,
  outlier = NA,
  tTest = FALSE,
  criterion = "aic",
  periods = NA,
  verbose = FALSE,
  stepwise = FALSE,
  p0 = NA,
  cLlik = TRUE,
  arma = TRUE
)

Arguments

y

a time series to forecast (it may be either a numerical vector or a time series object). This is the only input required. If a vector, the additional input periods should be supplied compulsorily (see below).

u

a matrix of input time series. If the output wanted to be forecast, matrix u should contain future values for inputs.

model

the model to estimate. It is a single string indicating the type of model for each component. It allows two formats "trend/seasonal/irregular" or "trend/cycle/seasonal/irregular". The possibilities available for each component are:

• Trend: ? / none / rw / irw / llt / dt;

• Seasonal: ? / none / equal / different;

• Irregular: ? / none / arma(0, 0) / arma(p, q) - with p and q integer positive orders;

• Cycles: ? / none / combination of positive or negative numbers.

  Positive numbers fix the period of the cycle while negative values estimate the period taking as initial condition the absolute value of the period supplied. Several cycles with positive or negative values are possible and if a question mark is included, the model test for the existence of the cycles specified (check the examples below).

h

forecast horizon. If the model includes inputs h is not used, the lenght of u is used instead.

outlier

critical level of outlier tests. If NA it does not carry out any outlier detection (default). A negative value indicates critical minimum t test for one run of outlier detection after identification. A positive value indicates the critical minium t test for outlier detection in any model during identification.

tTest

augmented Dickey Fuller test for unit roots (TRUE / FALSE). The number of models to search for is reduced, depending on the result of this test.

criterion

information criterion for identification ("aic", "bic" or "aicc").

periods

vector of fundamental period and harmonics.

verbose

intermediate results shown about progress of estimation (TRUE / FALSE).

stepwise

stepwise identification procedure (TRUE / FALSE).

p0

initial condition for parameter estimates.

cLlik

reserved input

arma

check for arma models for irregular components (TRUE / FALSE).

Value

An object of class UComp. It is a list with fields including all the inputs and the fields listed below as outputs. All the functions in this package fill in part of the fields of any UComp object as specified in what follows (function UC fills in all of them at once):

After running UCmodel or UCestim:

p

Estimated parameters

v

Estimated innovations (white noise in correctly specified models)

yFor

Forecasted values of output

yForV

Variance of forecasted values of output

criteria

Value of criteria for estimated model

After running UCvalidate:

table

Estimation and validation table

After running UCcomponents:

comp

Estimated components in matrix form

compV

Estimated components variance in matrix form

After running UCfilter, UCsmooth or UCdisturb:

yFit

Fitted values of output

yFitV

Variance of fitted values of output

a

State estimates

P

Variance of state estimates

aFor

Forecasts of states

PFor

Forecasts of states variances

After running UCdisturb:

eta

State perturbations estimates

eps

Observed perturbations estimates

Details

UCmodel is a function for modelling and forecasting univariate time series according to Unobserved Components models (UC). It sets up the model with a number of control variables that govern the way the rest of functions in the package will work. It also estimates the model parameters by Maximum Likelihood and forecasts the data. Standard methods applicable to UComp objects are print, summary, plot, fitted, residuals, logLik, AIC, BIC, coef, predict, tsdiag.

See Also

UC, UCvalidate, UCfilter, UCsmooth, UCdisturb, UCcomponents, UChp

Examples

# NOT RUN {
y <- log(AirPassengers)
m1 <- UCmodel(y)
m1 <- UCmodel(y, model = "llt/equal/arma(0,0)")
# }