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

1	Constant
2	Constant and trend

1	Akaike.
2	Schwarz.
3	t-stat significance.