kpss_1break¶

Purpose¶

Computes the KPSS stationary test with one structural break.

Format¶

{ kpss_stat, tb, lambda, cv } = KPSS_1break(y, model[, bwl, varm, trimm])¶

Parameters:

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

1

Break in level.

2

Break in level 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
trimm (Scalar) – Optional, trimming rate. Default = 0.10.

Returns:

kpss_stat (Scalar) – The KPSS test statistic.
tb (Scalar) – Location of break.
lambda (Scalar) – Break fraction (tb/T).
cv (Vector) – 1%, 5%, and 10% critical values for kpss_1break() statistic.

Examples¶

library tspdlib;

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

// Break in level
model = 1;
{ KPSS, tb1, lambda, cv } = KPSS_1break(y, model);

Source¶

kpss_1br.src

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

1	Break in level.
2	Break in level and trend.