Date: Wed, 13 Sep 2006 12:08:45 -0700
Reply-To: David L Cassell <davidlcassell@MSN.COM>
Sender: "SAS(r) Discussion" <SAS-L@LISTSERV.UGA.EDU>
From: David L Cassell <davidlcassell@MSN.COM>
Subject: Re: Nearest Neighbor Variance Estimation, Wang & Raftery
Content-Type: text/plain; format=flowed
>Wang and Raftery have a method for robust covariance estimation via
>nearest neighbor cleaning, called nearest neighbor variance estimation
>(NNVE), that they claim outperforms the minimum volume ellipsoid (MVE)
>SAS/IML has implemented MVE as a call. Wang has implemented a function
>for NNVE in R. Has anyone written or heard about SAS code for NNVE?
>-- TMK --
>"The Macro Klutz"
I have not heard anything about SAS code for NNVE. As soon as you
write some, you'll have a SUGI/SGF paper!
I think the key point of their work is in the case where the breakdown
value exceeds .50 so that even a median would be distorted by contaminating
data. This is entirely realistic in situation where samples come from more
than one distinct sub-population. (I see that a lot in survey sampling,
but a different approach is relevant with survey sample analysis.)
They are using a kth-nearest-neighbor approach, so clustering algorithms
may be the easiest way to tackle coding this up.
And finally, they are at U of Washington, home of S-Plus. Are they
allowed to write code in R? :-) :-)
David L. Cassell
3115 NW Norwood Pl.
Corvallis OR 97330
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