Re: [R] how to test robustness of correlation

From: Berton Gunter <gunter.berton_at_gene.com>
Date: Fri 27 Jan 2006 - 03:12:09 EST


Below

>
> Hi, Berton:
> thanks for getting back to me.
>
> I played around cor.rob(). Yes, I can get a robust
> correlation coefficient matrix based on mcd or mve outlier
> detection methods.
>
> I have two further questions:
>
> 1) How do I get a p value of the robust r?

A p-value for what? That r==0 ?

> 2) What I mean by resampling is "leave one out" procedure, to
> get a confidence interval of r. Do you know if there is any
> package in R to do it? I suppose I could code it myself,
> but it is nice if there is already one.
>
> thanks.
> Yang

**An** answer to both is the same -- bootstrap it. "Leave one out" is not resampling (/bootstrapping). It is usually referred to as "jackknifing," but that uses more specific ways of doing things than the analogy implies. Efron's little SIAM book on "The jackknife, bootstrap, etc. explains them and their relationships in detail. It is trivial to bootstrap cor.rob in base R using sample() (from the <x,y> **pairs** -- or n-tuples generally -- not the marginals separately ). If you insist on a package, "boot" is the obvious one -- why did you not attempt to find it yourself? Either way, expect it to take a while for a decent size resample (e.g. >1e4).


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