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 );
Library#
tsmt
Source#
selectlags.src