statsmodels.stats.stattools.robust_skewness  
statsmodels.stats.stattools.robust_skewness(y, axis=0) [source]
 
Calculates the four skewness measures in Kim & White    
Parameters:

 
y (array-like) –  
axis (int or None, optional) – Axis along which the skewness measures are computed. If None, the entire array is used.    
Returns:

 
sk1 (ndarray) – The standard skewness estimator. 
sk2 (ndarray) – Skewness estimator based on quartiles. 
sk3 (ndarray) – Skewness estimator based on mean-median difference, standardized by absolute deviation. 
sk4 (ndarray) – Skewness estimator based on mean-median difference, standardized by standard deviation.     Notes The robust skewness measures are defined  \[SK_{2}=\frac{\left(q_{.75}-q_{.5}\right) -\left(q_{.5}-q_{.25}\right)}{q_{.75}-q_{.25}}\]  \[SK_{3}=\frac{\mu-\hat{q}_{0.5}} {\hat{E}\left[\left|y-\hat{\mu}\right|\right]}\]  \[SK_{4}=\frac{\mu-\hat{q}_{0.5}}{\hat{\sigma}}\]  
[*]
Tae-Hwan Kim and Halbert White, “On more robust estimation of skewness and kurtosis,” Finance Research Letters, vol. 1, pp. 56-73, March 2004.
  


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