lagreport

Purpose

Compute and graph the autocorrelation function and partial autocorrelation function for a time series.

Format

{ acf, pacf } = lagreport(y, lags, diff)

Parameters:

• y (Tx1 matrix) – time series data.

• lags (scalar) – Optional, max number of lags to test. Default = 10.

• diff (scalar) – Optional, if non-zero data is first differenced. Default - 0.

Returns:

• acf (matrix) – autorcorrelation function.

• pacf (matrix) – partial autorcorrelation function.

Example

new;
cls;
library tsmt;

// Simulate data
b = { 0.5, -0.3 };
p = 2;
q = 0;
const = 5;
trend = 0.05;
n = 500;
k = 1;
std = 1;
seed = 10191;

yt = simarmamt(b, p, q, const, trend, n, k, std, seed);

//  Call lag report
{ acf1, pacf1 } = lagreport(yt);

The results printed to screen read:

Lags          ACF
 0.00         0.98
 1.00         0.96
 2.00         0.95
 3.00         0.95
 4.00         0.95
 5.00         0.94
 6.00         0.93
 7.00         0.92
 8.00         0.92
 9.00         0.91
 Lags         PACF
 1.00         0.98
 2.00         0.03
 3.00         0.28
 4.00         0.17
 5.00         0.14
 6.00         0.02
 7.00        -0.05
 8.00        -0.04
 9.00         0.00
10.00         0.05

Library

tsmt

Source

lagreport.src