adf#

Purpose#

Computes the Augmented Dickey-Fuller unit root test.

Format#

{ tstat, lags, cv } = adf(y, model[, pmax, ic])#
Parameters:
  • y (Nx1 matrix) – Time series data to be tested.

  • model (Scalar) –

    Model to be implemented.

    0

    No constant or trend.

    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:
  • tstat (Scalar) – Dickey-Fuller test statistic.

  • lags (Scalar) – Number of lags selected by chosen information criterion.

  • cv (Vector) – 1%, 5%, and 10% critical values for ADF \(\tau\)-stat.

Examples#

library tspdlib;

// Load date file
y = loadd(getGAUSSHome() $+ "pkgs/tspdlib/examples/ts_examples.csv", "Y");

// No deterministic component
model = 0;

// Call ADF test
{ ADFtau, ADFp, cvADF } = ADF(y, model);

Source#

adf.src

See also

Functions adf_1br(), adf_2br()