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SUMMARY:linear interpolation through missing data

To: "S-PLUS Newsgroup" <s-news@lists.biostat.wustl.edu>
Subject: SUMMARY:linear interpolation through missing data
From: "Lambert.Winnie" <lambert.winnie@ensco.com>
Date: Wed, 25 Aug 2004 12:27:50 -0400
Thread-index: AcSKOGe0ZA4I7DdqR2Wjd+TYGFJTgQAh0baA
Thread-topic: SUMMARY:linear interpolation through missing data
Thanks to David Parkhurst and Sundar Dorai-Raj for responding with
suggestions.  Sundar's solution did exactly what I needed.  I would have
never thought to search for approx()!

The original email is next, followed by Sundar's response.  Thanks
again.

Win Lambert

> S-PLUS6 on Windows XP
>  
> I found this question in 3 emails in the archive, but did not see an 
> answer.  I have looked in my S-PLUS books, but perhaps am looking in 
> the wrong place for the wrong thing.  I want to do a relatively simple

> linear interpolation across missing values in a vector, e.g.  ...850 
> 862
> 875 NA NA 927 946... weighted by another non-missing (and never
> missing!) variable.  Is there a function for this?  If not, I can 
> trudge through and figure out an algorithm, but would rather not waste

> time if I can do it in a one-liner.
>  
> Thanks much.
>  

Try ?approx. You'll need to supply an `x' but here's an example to help:

set.seed(1)
n <- 100
y <- sort(rnorm(n))
x <- seq(n)
na <- sample(n, 3) # remove 3 points
guess <- approx(x[-na], y[-na], xout = x[na])$y cbind(true = y[na],
guess)

--sundar




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