# 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