auto.arima(x, d=NA, D=NA, max.p=5, max.q=5,
max.P=2, max.Q=2, max.order=5, start.p=2, start.q=2,
start.P=1, start.Q=1, stationary=FALSE,
ic=c("aic","aicc", "bic"), stepwise=TRUE, trace=FALSE,
approximation=(length(x)>100 | frequency(x)>12), xreg=NULL,
test=c("kpss","adf","pp"), seasonal.test=c("ocsb","ch"),
allowdrift=TRUE, lambda=NULL)
TRUE
, restricts search to stationary models.TRUE
, will do stepwise selection (faster). Otherwise, it searches over all models. Non-stepwise selection can be very slow, especially for seasonal models.TRUE
, the list of ARIMA models considered will be reported.TRUE
, estimation is via conditional sums of squares andthe information criteria used for model selection are approximated. The final model is still computed using maximum likelihood estimation. Approximation should be used for long time sendiffs
for details.nsdiffs
for details.TRUE
, models with drift terms are considered.arima
Arima
fit <- auto.arima(WWWusage)
plot(forecast(fit,h=20))
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