Box-Pierce test
Overview
The Box-Pierce test checks the “overall” randomnes of a time series using a given number of autocorrelations.
It tests wether any of a group of autocorrelations of a time series are significantly different from 0.
Algorithm
We consider the autocorrelations $\hat\gamma_l, \cdots, \hat\gamma_{l\cdot k}$. Typically, $l=1$ when testing the independence of the series or $l=freq$ when testing seasonality.
The value of the test is defined by
\[bp=n \sum_{i=1}^k\hat\gamma_{i \cdot l}^2\]It is asymptotically distributed as a $\chi \left(k\right)$
Implementation
This test is implemented in the class demetra.stats.tests.BoxPierceTest
Example
int N=100;
DataBlock sample=DataBlock.make(N);
Random rnd=new Random();
sample.set(rnd::nextDouble);
BoxPierceTest bp=new BoxPierceTest(sample);
StatisticalTest test = bp
.lag(3)
.autoCorrelationsCount(10)
.build();