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1. Vectorizing nested for loops (score: 1)
Author: joseph <joseph468@yahoo.com>
Date: Mon, 4 Aug 2003 08:26:28 -0700 (PDT)
Dear list members: The following code is a reduced version of a larger problem: x <- c(5,6,7,8) y <- c(1,2,3,4) z <- matrix(NA, nrow=length(x), ncol=length(y)) for(i in 1:4){ for(j in 1:4){ z[i,j] <-
/archives/html/s-news/2003-08/msg00020.html (7,741 bytes)

2. Summary: Vectorizing nested for loops. (score: 1)
Author: joseph <joseph468@yahoo.com>
Date: Tue, 12 Aug 2003 05:55:09 -0700 (PDT)
I wish to acknowledge and thank all those who responded to my problem of vectorizing nested ?for? loops (see summary below). In particular, I wish to thank Jeffrey Wang, Ted Wright, Tony Plate, John
/archives/html/s-news/2003-08/msg00065.html (9,244 bytes)

3. Epheremal data tool tips and point labels (score: 1)
Author: joseph <joseph468@yahoo.com>
Date: Thu, 26 Jun 2003 07:39:50 -0700 (PDT)
Whenever I make a graph of some data and move my cursor over any specific data point a box usually appears giving specific info about that particular data point. It usually disappears after about 3 s
/archives/html/s-news/2003-06/msg00194.html (6,913 bytes)

4. Approximate Entropy implementation in SPlus or R (score: 1)
Author: joseph <joseph468@yahoo.com>
Date: Tue, 24 Jul 2007 18:05:50 -0700 (PDT)
Dear List Members: Approximate Entropy (ApEn) is a regularity statistic that quantifies the unpredictability of fluctuations in a time series. ApEn reflects the likelihood that similar patterns of ob
/archives/html/s-news/2007-07/msg00028.html (8,113 bytes)

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