Testing for autocorrelation in time series data
Autocorrelation is like statistical correlation (think Pearson correlation from high school), which measures the strength of a linear relationship between two variables, except that we measure the linear relationship between time series values separated by a lag. In other words, we are comparing a variable with its lagged version of itself.
In this recipe, you will perform a Ljung-Box test to check for autocorrelations up to a specified lag and whether they are significantly far off from 0. The null hypothesis for the Ljung-Box test states that the previous lags are not correlated with the current period. In other words, you are testing for the absence of autocorrelation.
When running the test using acorr_ljungbox from statsmodels, you need to provide a lag value. The test will run for all lags up to the specified lag (maximum lag).
The autocorrelation test is another helpful test for model diagnostics. As discussed in the...
