[R] code optimization
james.holtman@convergys.com
james.holtman at convergys.com
Mon Apr 29 19:32:33 CEST 2002
Try this:
split(delta,cut(delta, breaks=c(0,2,4,7,10,max(delta)),include.lowest=T))
$"[0,2]"
[1] 0.0 1.4 2.0 2.0
$"(2,4]"
[1] 2.3 2.3
$"(4,7]"
[1] 4.5 6.4
$"(7,10]"
[1] 8.9 7.4
$"(10,12.4]"
[1] 12.4 11.5
"Peter B. Mandeville" <mandevip at uaslp.mx>@stat.math.ethz.ch on 06/24/2002
13:11:41
Sent by: owner-r-help at stat.math.ethz.ch
To: r-help at stat.math.ethz.ch
cc:
Subject: [R] code optimization
I have a function "eval.delta" which does what I want but isn't very
elegant. I have consulted the R documents, MASS, and S Programming. Is
there a practical way to optimize the code? Thank you very much.
Peter B.
Function:
eval.delta <- function(delta){
cat("VALUES\n")
vlr <- NULL
k <- 0
for(j in 1:length(delta)) if(delta[j] <= 2){
k <- k+1
vlr[k] <- delta[j]
}
cat("<= 2 (no credible evidence)\t",k,"\t",vlr,"\n")
vlr <- NULL
k <- 0
for(j in 1:length(delta)) if(delta[j]>2 & delta[j] <= 4){
k <- k+1
vlr[k] <- delta[j]
}
cat("> 2 y <= 4 (weak evidence)\t",k,"\t",vlr,"\n")
vlr <- NULL
k <- 0
for(j in 1:length(delta)) if(delta[j]>4 & delta[j] <= 7){
k <- k+1
vlr[k] <- delta[j]
}
cat("> 4 y <= 7 (definite evidence)\t",k,"\t",vlr,"\n")
vlr <- NULL
k <- 0
for(j in 1:length(delta)) if(delta[j]>7 & delta[j] <= 10){
k <- k+1
vlr[k] <- delta[j]
}
cat("> 7 y <= 10 (strong evidence)\t",k,"\t",vlr,"\n")
vlr <- NULL
k <- 0
for(j in 1:length(delta)) if(delta[j]>10){
k <- k+1
vlr[k] <- delta[j]
}
cat("> 10 (very strong evidence)\t",k,"\t",vlr,"\n")
cat("\nMODELS\n")
vlr <- NULL
k <- 0
for(j in 1:length(delta)) if(delta[j] <= 2){
k <- k+1
vlr[k] <- j
}
cat("<= 2 (no credible evidence)\t",k,"\t",vlr,"\n")
vlr <- NULL
k <- 0
for(j in 1:length(delta)) if(delta[j]>2 & delta[j] <= 4){
k <- k+1
vlr[k] <- j
}
cat("> 2 y <= 4 (weak evidence)\t",k,"\t",vlr,"\n")
vlr <- NULL
k <- 0
for(j in 1:length(delta)) if(delta[j]>4 & delta[j] <= 7){
k <- k+1
vlr[k] <- j
}
cat("> 4 y <= 7 (definite evidence)\t",k,"\t",vlr,"\n")
vlr <- NULL
k <- 0
for(j in 1:length(delta)) if(delta[j]>7 & delta[j] <= 10){
k <- k+1
vlr[k] <- j
}
cat("> 7 y <= 10 (strong evidence)\t",k,"\t",vlr,"\n")
vlr <- NULL
k <- 0
for(j in 1:length(delta)) if(delta[j]>10){
k <- k+1
vlr[k] <- j
}
cat("> 10 (very strong evidence)\t",k,"\t",vlr,"\n")
}
Data:
> delta <- c(0,1.4,2.3,4.5,2.3,8.9,12.4,6.4,7.4,11.5,2,2)
Function Call and Output:
> eval.delta(delta)
VALUES
<= 2 (no credible evidence) 4 0 1.4 2 2
> 2 y <= 4 (weak evidence) 2 2.3 2.3
> 4 y <= 7 (definite evidence) 2 4.5 6.4
> 7 y <= 10 (strong evidence) 2 8.9 7.4
> 10 (very strong evidence) 2 12.4 11.5
MODELS
<= 2 (no credible evidence) 4 1 2 11 12
> 2 y <= 4 (weak evidence) 2 3 5
> 4 y <= 7 (definite evidence) 2 4 8
> 7 y <= 10 (strong evidence) 2 6 9
> 10 (very strong evidence) 2 7 10
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