Hi,
maybe the following code helps to achieve what you want?
It seems to me it is basically a 'recode' question.
set.seed(1234) # not neccessary but this ensures we have the same
#results
random.values <- runif(n=30, min=0, max=100)
newgrouping <- cut(x=random.values, breaks=c(0,0.1, 1, 2, 5, 10, 25,
50, 75, 95, 100), labels=1:10)
cbind(random.values,newgrouping)
## should result in:
random.values newgrouping
[1,] 11.3703411 6
[2,] 62.2299405 8
[3,] 60.9274733 8
[4,] 62.3379442 8
[5,] 86.0915384 9
[6,] 64.0310605 8
[7,] 0.9495756 2
[8,] 23.2550506 6
[9,] 66.6083758 8
[10,] 51.4251141 8
[11,] 69.3591292 8
[12,] 54.4974836 8
[13,] 28.2733584 7
[14,] 92.3433484 9
etc.
I hope this helps,
Roland
Wade Wall wrote:
Hi all,
I am trying to convert geometric means in a matrix to cover classes. My
values are as such:
perc<-c(0,0.025136418, 0.316227766, 1.414213562,3.16227766, 7.071067812,
15.8113883, 35.35533906, 61.23724357, 84.40971508, 97.46794345)
cover<-c(0,1,2,3,4,5,6,7,8,9,10)
This is what I am trying to accomplish
veg_mean[veg_mean>0 && veg_mean < .1] <- 1
veg_mean[veg_mean>= .1 && veg_mean < 1.0] <- 2
veg_mean[veg_mean>=1.0 && veg_mean < 2.0] <- 3
veg_mean[veg_mean>=2.0 && veg_mean < 5.0] <- 4
veg_mean[veg_mean>= 5.0 && veg_mean < 10.0] <- 5
veg_mean[veg_mean>= 10.0 && veg_mean < 25] <- 6
veg_mean[veg_mean>= 25.0 && veg_mean < 50.0] <- 7
veg_mean[veg_mean>=50.0 && veg_mean < 75.0] <- 8
veg_mean[veg_mean>= 75.0 && veg_mean < 95.0 ] <- 9
veg_mean[veg_mean>= 95.0 && veg_mean <= 100] <- 10
veg_mean[veg_mean> 100] <- NA
where values are assigned based on the geometric means. However, I think
that my syntax for the && operator is wrong and I can't find a reference to
proper syntax. I basically want to "bin" the geometric means.
Any help would be greatly appreciated.
Thanks,
Wade
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