[R-SIG-Finance] Winsorization

[Tobias Verbeke]

Adams, Zeno wrote:

> 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.

For a structured overview of robust methods available in R,
see the robust statistics task view at

http://cran.r-project.org/web/views/Robust.html

HTH,
Tobias

> 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 at stat.math.ethz.ch on behalf of ???
> Sent: Thu 9/18/2008 5:29 AM
> To: r-sig-finance at 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
> 
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