fourier_kpss#
Purpose#
Computes the KPSS stationarity test with flexible Fourier form structural breaks.
Format#
- { KPSSk, f, cv } = fourier_kpss(y, model[, fmax, bwl, varm])#
- Parameters:
y (Nx1 matrix) – Dependent variable.
model (Scalar) –
Model to be implemented.
1
Constant
2
Constant and trend
fmax (Scalar) – Optional, maximum number of single Fourier frequency (upper bound is 5). Default = 5.
bwl (Scalar) – Optional, bandwidth for spectral window. Default = round(4 * (T/100)^(2/9)).
varm (Scalar) –
Optional, long-run consistent variance estimation method. Default = 1.
1
iid
2
Bartlett
3
Quadratic Spectral (QS)
4
SPC with Bartlett (Sul, Phillips & Choi, 2005)
5
SPC with QS
6
Kurozumi with Bartlett
7
Kurozumi with QS
- Returns:
KPSSk (Scalar) – KPSS(k) statistic.
f (Scalar) – Number of single frequency.
cv (Vector) – 1%, 5%, 10% critical values for the chosen model
Examples#
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
{ KPSSk, f, cv } = Fourier_KPSS(y, model);
Source#
fourier_kpss.src
See also
Functions fourier_adf()
, fourier_gls()
, fourier_lm()