erspt¶
Purpose¶
Computes the ERS point optimal unit root test.
Format¶
-
{ Pt, lrv, cvPT } =
ERSpt(y, model[, bwl, varm])¶ Parameters: - y (Nx1 matrix) – Time series data to be tested.
- model (Scalar) –
Model to be implemented.
1 Constant. 2 Constant and trend. - bwl (Scalar) – Optional, bandwidth for the 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: - Pt (Scalar) – Point statistic
- lrv (Scalar) – Long-run variance estimate.
- cvPt (Vector) – 1%, 5%, and 10% critical values for Pt.
Examples¶
library tspdlib;
// Load date file
y = loadd(getGAUSSHome() $+ "pkgs/tspdlib/examples/ts_examples.csv", "Y");
// With constant
model = 1;
// Call test
{ Pt, lrv, cvPt } = ERSpt(y, model);