statsmodels.regression.recursive_ls.RecursiveLSResults.cusum_squares¶
- RecursiveLSResults.cusum_squares¶
Cumulative sum of squares of standardized recursive residuals statistics
- Returns:
- cusum_squaresarray_like
An array of length nobs - k_exog holding the CUSUM of squares statistics.
Notes
The CUSUM of squares statistic takes the form:
\[s_t = \left ( \sum_{j=k+1}^t w_j^2 \right ) \Bigg / \left ( \sum_{j=k+1}^T w_j^2 \right )\]where \(w_j\) is the recursive residual at time \(j\).
Excludes the first k_exog datapoints.
References