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