Runs all relevant functions for ARIMA modelling
ARIMA(
y,
u = NULL,
model = NULL,
cnst = NULL,
s = frequency(y),
criterion = "bic",
h = 2 * s,
verbose = FALSE,
lambda = 1,
maxOrders = c(3, 2, 3, 2, 1, 2),
bootstrap = FALSE,
nSimul = 5000,
fast = FALSE
)
An object of class ARIMA
. See ARIMAforecast
.
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 s
should be supplied compulsorily (see below).
a matrix of input time series. If
the output wanted to be forecast, matrix u
should contain future values for inputs.
the model to estimate. A vector c(p,d,q,P,D,Q) containing the model orders of an ARIMA(p,d,q)x(P,D,Q)_s model. A constant may be estimated with the cnst input. Use a NULL to automatically identify the ARIMA model.
flag to include a constant in the model (TRUE/FALSE/NULL). Use NULL to estimate
seasonal period of time series (1 for annual, 4 for quarterly, ...)
information criterion for identification stage ("aic", "bic", "aicc")
forecast horizon. If the model includes inputs h is not used, the lenght of u is used instead.
intermediate estimation output (TRUE / FALSE)
Box-Cox lambda parameter (NULL: estimate)
a vector c(p,d,q,P,D,Q) containing the maximum orders of model orders to search for in the automatic identification
use bootstrap simulation for predictive distributions
number of simulation runs for bootstrap simulation of predictive distributions
fast identification (avoids post-identification checks)
Diego J. Pedregal
See help of ARIMAforecast
.
ARIMAforecast
, ARIMAvalidate
,
if (FALSE) {
y <- log(AirPAssengers)
m1 <- ARIMA(y)
m1 <- ARIMA(y, lambda = NULL)
}
Run the code above in your browser using DataLab