y
.ets(y, model="ZZZ", damped=NULL, alpha=NULL, beta=NULL, gamma=NULL, phi=NULL,
additive.only=FALSE, lower=c(rep(0.0001,3), 0.8), upper=c(rep(0.9999,3),0.98),
opt.crit=c("lik","amse","mse","sigma"), nmse=3,
bounds=c("both","usual","admissible"), ic=c("aic","aicc","bic"),
restrict=TRUE)
ic
) returned.nmse
forecast horizons), "sigma"
(Standard deviation of residuals), or "lik" (Log-likelihood, the default).nmse=
"usual"
indicates all parameters must lie between specified lower and
upper bounds; "admissible"
indicates parameters must lie in the
admissible space; "both"
(default) takes theets
".
The generic accessor functions fitted.values
and residuals
extract useful features of
the value returned by ets
and associated functions.HoltWinters
, rwf
, arima
.fit <- ets(USAccDeaths)
plot(forecast(fit))
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