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Medcouple : ウィキペディア英語版
Medcouple

The medcouple is a robust statistic that measures the skewness of a univariate distribution.〔 Its robustness makes it suitable for identifying outliers in adjusted boxplots.〔〔 Ordinary boxplots do not fare well with skew distributions, since they label the longer unsymmetrical tails as outliers. Using the medcouple, the whiskers of a boxplot can be adjusted for skew distributions and thus have a more accurate identification of outliers for non-symmetrical distributions.
As a kind of order statistic, the medcouple belongs to the class of incomplete generalised L-statistics.〔 Like the ordinary median or mean, the medcouple is a nonparametric statistic, thus it can be computed for any distribution.
== Definition ==

In order to harmonise with zero-based indexing in many programming languages, we will index from zero in all that follows.
Let X := x_0 \geq x_1 \geq \ldots \geq x_ be an ordered sample of size n, and let x_m be the median of X. Define the sets
::X^+ := \,
::X^- := \,
of sizes p := |X^+| and q := |X^-| respectively. For x_i^+ \in X^+ and x_j^- \in X^-, we define the ''kernel function''
:h(x_i^+, x_j^-) := \begin
\displaystyle\frac & \text x_i^+ > x_j^-, \\
\operatorname (p - 1 - i - j) & \text x_i^+ = x_m = x_j^-,
\end
where \operatorname is the sign function.
The ''medcouple'' is then the median of the set〔
:: \.
In other words, we split the distribution into all values greater or equal to the median and all values less than or equal to the median. We define a kernel function whose first variable is over the p greater values and whose second variable is over the q lesser values. For the special case of values tied to the median, we define the kernel by the signum function. The medcouple is then the median over all pq values of h(x_i^+, x_j^-).
Since the medcouple is not a median applied to all (x_i, x_j) couples, but only to those for which x_i^+ \geq x_m \geq x_j^-, it belongs to the class of incomplete generalised L-statistics.〔

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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