
 

what method are you planning to use?

If you want to do a regression analysis, there are better methods for this.
The quantreg package can give you the least absolute deviation (LAD) estimate, (this corresponds to a quantile regression with the quantile tau = 0.5)
which is robust to outliers.
Another interesting approach is weighted least squares available in S-Plus. 
See Martin, R. and Simin, T. (2003) "Outlier-Resistant Estimates of Beta" Financial Analysts Journal, September, pp. 56-69.

Zeno


-----Original Message-----
From: r-sig-finance-bounces@stat.math.ethz.ch on behalf of ???
Sent: Thu 9/18/2008 5:29 AM
To: r-sig-finance@stat.math.ethz.ch
Subject: [R-SIG-Finance] Winsorization
 
Dear all,
       I am dealing with a data set with many outliers value. And it is said
that a technique named winsorization or winsorising can
reduce the influence of those extreme values. Did anyone use this skill
before? And how to do it in S+ or R? Thank you.

Zhigang Liu

	[[alternative HTML version deleted]]

_______________________________________________
R-SIG-Finance@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-sig-finance
-- Subscriber-posting only.
-- If you want to post, subscribe first.





EBS European Business School gemeinnuetzige GmbH - Sitz der Gesellschaft: Wiesbaden, Amtsgericht Wiesbaden HRB 19951 - Umsatzsteuer-ID DE 113891213 Geschaeftsfuehrung: Prof. Dr. Christopher Jahns, Rektor; Dr. Reimar Palte, Kanzler;  Sabine Fuchs, Prokuristin; Verwaltungsrat: Dr. Hellmut K. Albrecht, Vorsitzender

	[[alternative HTML version deleted]]

