# selectLags#

## Purpose#

Select lags based on method of statistical inference.

## Format#

{ stat, p_mat } = selectLags(y, x, maxlag, method, print_out)#
Parameters:
• y (Matrix) – Nx1 data to be tested.

• x (Matrix) – NxK, exogenous regressor. Set equal to 0 if there are no exogenous variables.

• maxlag (Scalar) – maximum lags.

• method (String) –

lag selection method:

 AIC Akaike information criterion. BIC Bayesian information criterion. HQC Hannan-Quinn criterion. FPE Final prediction error. ALL All methods computed.

Returns:
• stat (matrix) – lag selection criterion values.

• p_mat (matrix) – optimal VAR lags.

## Example#

```new;
cls;
library tsmt;

// Use the simarmamt procedure to generate ar data
// This generates 1000 observations of and
// AR(4) series with a constant
// and standard deviation equal to 1.
b = { 0.1, .3, -.4, 0.2 };
q = 0;
p = 4;
const = 1;
tr = 0;
n = 1000;
k = 1;
std = 1;
seed = 19786;

y = simarmamt( b, p, q, const, tr, n, k, std, seed );

// Set parameters for the simarmamt procedure
// Exogenous variables -- Add intercept
x = ones( rows(y), 1 );

// Max number of lags to test for
p = 8;

// Method to test
method = "AIC";
printOut =1 ;

{ stat , p_mat } = selectLags( y, x, p, method, printOut );

// Method to test
method = "ALL";

{ stat_all , p_mat_all } = selectLags( y, x, p, method, printOut );
```

tsmt

selectlags.src