statsmodels.stats.stattools.robust_skewness¶
-
statsmodels.stats.stattools.robust_skewness(y, axis=0)[source]¶ Calculates the four skewness measures in Kim & White
- Parameters
- yarray-like
- axisint or None, optional
Axis along which the skewness measures are computed. If None, the entire array is used.
- Returns
- sk1ndarray
The standard skewness estimator.
- sk2ndarray
Skewness estimator based on quartiles.
- sk3ndarray
Skewness estimator based on mean-median difference, standardized by absolute deviation.
- sk4ndarray
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.