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From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
Re: st: Computing medcouple |

Date |
Wed, 12 Aug 2009 20:33:32 +0100 |

This sounds a little similar in spirit to using L-moments to calculate a skewness measure. The latter approach arguably has two features: it is systematic and it is already implemented in Stata through -lmoments- from SSC. As far as medcouple is concerned, you could compute it exactly or by sampling. I've no code to offer. My prejudice here is that for most problems you would be better off either transforming the data or using a graph form that discarded less of the information than a box plot does. Otherwise put, if the data are very skew you usually need to see more detail about the tails than a boxplot provides. Nick n.j.cox@durham.ac.uk Ronnie Babigumira <rb.glists@gmail.com> Vandervieren and Hubert (2004) present what they call a robust measure of skewness using the medcouple Given a distribution F, medcouple (MC(F)) is defined as MC(F) = med h(xi,xj) given xi<med<xj where - h = (xj-m_F)-(m_F-xi) ----------------- xj-xi - m_F is the median of F I would like to compute MC but dont know how to even start. Any pointers will be much appreciated. Ronnie Reference Vanderviere, E. & Huber, M. (2004). An adjusted boxplot for skewed distributions. In J. Antoch (Ed.), COMPSTAT2004 Symposium: proceedings in computational statistics (pp. 1933-1940). Heidelberg, Germany: Physica-Verlag. The paper can be downloaded here http://wis.kuleuven.be/stat/robust/Papers/boxplotCOMPSTAT04.pdf * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**Re: st: Computing medcouple***From:*Ronnie Babigumira <rb.glists@gmail.com>

**RE: st: Computing medcouple***From:*"Lachenbruch, Peter" <Peter.Lachenbruch@oregonstate.edu>

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