UCestim {UComp} | R Documentation |
UCestim
Description
Estimates and forecasts UC models
Usage
UCestim(sys)
Arguments
sys |
an object of type |
Details
UCestim
estimates and forecasts a time series using an
UC model.
The optimization method is a BFGS quasi-Newton algorithm with a
backtracking line search using Armijo conditions.
Parameter names in output table are the following:
Damping: Damping factor for DT trend.
Level: Variance of level disturbance.
Slope: Variance of slope disturbance.
Rho(#): Damping factor of cycle #.
Period(#): Estimated period of cycle #.
Var(#): Variance of cycle #.
Seas(#): Seasonal harmonic with period #.
Irregular: Variance of irregular component.
AR(#): AR parameter of lag #.
MA(#): MA parameter of lag #.
AO#: Additive outlier in observation #.
LS#: Level shift outlier in observation #.
SC#: Slope change outlier in observation #.
Beta(#): Beta parameter of input #.
Cnst: Constant.
Standard methods applicable to UComp objects are print, summary, plot, fitted, residuals, logLik, AIC, BIC, coef, predict, tsdiag.
Value
The same input object with the appropriate fields filled in, in particular:
p: Estimated transformed parameters
v: Estimated innovations (white noise in correctly specified models)
yFor: Forecast values of output
yForV: Forecasted values variance
criteria: Value of criteria for estimated model
covp: Covariance matrix of estimated transformed parameters
grad: Gradient of log-likelihood at the optimum
iter: Estimation iterations
Author(s)
Diego J. Pedregal
See Also
UC
, UCmodel
, UCvalidate
, UCfilter
,
UCsmooth
, UCdisturb
, UCcomponents
,
UChp
Examples
## Not run:
m1 <- UCsetup(log(AirPassengers))
m1 <- UCestim(m1)
## End(Not run)