UComp (version 5.1)

ARIMAsetup: ARIMAsetup

Description

Sets up ARIMA general models

Usage

ARIMAsetup(
  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
)

Value

An object of class ARIMA. See ARIMAforecast.

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 s 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. 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.

cnst

flag to include a constant in the model (TRUE/FALSE/NULL). Use NULL to estimate

s

seasonal period of time series (1 for annual, 4 for quarterly, ...)

criterion

information criterion for identification stage ("aic", "bic", "aicc")

h

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

verbose

intermediate estimation output (TRUE / FALSE)

lambda

Box-Cox lambda parameter (NULL: estimate)

maxOrders

a vector c(p,d,q,P,D,Q) containing the maximum orders of model orders to search for in the automatic identification

bootstrap

use bootstrap simulation for predictive distributions

nSimul

number of simulation runs for bootstrap simulation of predictive distributions

fast

fast identification (avoids post-identification checks)

Author

Diego J. Pedregal

Details

See help of ARIMAforecast.

See Also

ARIMA, ARIMAforecast, ARIMAvalidate,

Examples

if (FALSE) {
y <- log(AirPAssengers)
m1 <- ARIMAsetup(y)
m1 <- ARIMAsetup(y, lambda = NULL)
}