stats.sandwich_covariance.cov_hac()
statsmodels.stats.sandwich_covariance.cov_hac
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statsmodels.stats.sandwich_covariance.cov_hac(results, nlags=None, weights_func=<function weights_bartlett>, use_correction=True) -
heteroscedasticity and autocorrelation robust covariance matrix (Newey-West)
Assumes we have a single time series with zero axis consecutive, equal spaced time periods
Parameters: results : result instance
result of a regression, uses results.model.exog and results.resid TODO: this should use wexog instead
nlags : int or None
highest lag to include in kernel window. If N