ralsadf#

Purpose#

Computes the Augmented Dickey-Fuller unit root test with the RALS technique for non-normal errors.

Format#

{ rals_tau, rho2, cv } = ralsadf(y, model[, pmax, ic])#

Parameters:

y (Nx1 matrix) – Time series data to be tested.
model (Scalar) –
Model to be implemented.

1

Constant.

2

Constant and trend.
pmax (Scalar) – Optional, the maximum number of lags for \(\Delta y\). Default = 8.
ic (Scalar) –
Optional, the information criterion used for choosing lags. Default = 3.

1

Akaike.

2

Schwarz.

3

t-stat significance.

Returns:

rals_tau (Scalar) – The tau statistic based on RALS procedure and ADF test.
rho2 (Scalar) – The estimated rho square.
cv (Vector) – 1%, 5%, and 10% critical values for the estimated rho2

Examples#

library tspdlib;

// Load date file
y = loadd(getGAUSSHome() $+ "pkgs/tspdlib/examples/TSe.dat");

// With constant
model = 1;
{ rals_tau, rho2, cv } = RALSADF(y, model);

Source#

rals_adf.src

1	Constant.
2	Constant and trend.

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