arimaControlCreate#

Purpose#

Create an arimaControl structure with default values.

Format#

ctl = arimaControlCreate()#

Returns:

ctl (struct) –

An instance of an arimaControl structure with the following default values:

ctl.max_p

Scalar, maximum AR order for auto-selection. Default = 5.

ctl.max_q

Scalar, maximum MA order for auto-selection. Default = 5.

ctl.max_d

Scalar, maximum differencing order. Default = 2.

ctl.max_bp

Scalar, maximum seasonal AR order. Default = 2.

ctl.max_bq

Scalar, maximum seasonal MA order. Default = 2.

ctl.max_bd

Scalar, maximum seasonal differencing order. Default = 1.

ctl.max_order

Scalar, maximum total order (p+q+P+Q). Default = 5.

ctl.ic

String, information criterion for auto-selection.

`"aicc"`	Corrected Akaike. (Default)
`"aic"`	Akaike.
`"bic"`	Bayesian (Schwarz).

ctl.stepwise

Scalar, search strategy for auto-selection.

1	Stepwise search (faster, recommended). (Default)
0	Exhaustive search (slower, guaranteed global optimum).

ctl.method

String, estimation method.

`"css-ml"`	CSS for starting values, then ML refinement. (Default)
`"ml"`	Maximum likelihood only.

ctl.include

String, deterministic terms.

`"auto"`	Automatic: mean if d=0, drift if d=1, none if d>=2. (Default)
`"mean"`	Force include mean.
`"drift"`	Force include drift.
`"none"`	No deterministic term.

ctl.quiet

Scalar, output control. Set to 1 to suppress printed output. Default = 0.

ctl.max_iter

Scalar, maximum optimizer iterations. Default = 1000.

ctl.tol

Scalar, convergence tolerance. Default = 1e-8.

Examples#

new;
library timeseries;

// Create control structure with defaults
ctl = arimaControlCreate();

// Customize: BIC selection, ML estimation
ctl.ic = "bic";
ctl.method = "ml";

// Use with arimaFit
y = loadd(getGAUSSHome("pkgs/timeseries/examples/airline.dat"), "passengers");
result = arimaFit(y, ctl, season=12);

Remarks#

All members of the arimaControl structure apply only to auto-selection. When a fixed order is passed to arimaFit(), the search-related members (max_p, max_q, max_d, ic, stepwise, etc.) are ignored.

Library#

timeseries

Source#

arima.src