fourier_gls¶
Purpose¶
Local generalized least squares unit root test with flexible Fourier form structural breaks.
Format¶
-
{ GLSk, k, p, cv } =
fourier_gls
(y, model[, pmax, fmax, ic])¶ - Parameters:
y (Nx1 matrix) – Dependent variable.
model (Scalar) –
Model to be implemented.
1
Constant
2
Constant and trend
pmax (Scalar) – Maximum number of lags for \(\Delta y\); 0=no lag.
fmax (Scalar) – Maximum number of single Fourier frequency (upper bound is 5).
ic (Scalar) –
Optional, the information criterion used for choosing lags. Default = 3.
1
Akaike.
2
Schwarz.
3
t-stat significance.
- Returns:
GLSk (Scalar) – GLS(k) statistic.
k (Scalar) – Number of single frequency.
p (Scalar) – number of lags selected by chosen information criterion
cv (Vector) – 1%, 5%, 10% critical values for the chosen model
Examples¶
new;
cls;
library tspdlib;
// Load date file
y = loadd(getGAUSSHome() $+ "pkgs/tspdlib/examples/ts_examples.csv", "Y + date($Date, '%b-%y')");
// With constant
model = 1;
// Call test
{ GLSstat, f, p, cv } = Fourier_GLS(y, model);
Source¶
fourier_gls.src
See also
Functions fourier_adf()
, fourier_kpss()
, fourier_lm()