Hi. I searched the list and didn't found nothing similar to this. I simplified
my example like below:
#I need calculate correlation (for example) between 2 columns classified by a
third one at a data.frame, like below:
#number of rows
nr = 10
#the third column is to enforce that I need correlation on two variables only
dataf =
as.data.frame(matrix(c(rnorm(nr),rnorm(nr)*2,runif(nr),sort(c(1,1,2,2,3,3,sample(1:3,nr-6,replace=TRUE)))),ncol=4))
names(dataf)[4] = "class"
#> dataf
# V1 V2 V3 class
#1 0.56933020 1.2529931 0.30774422 1
#2 0.41702299 -1.6441547 0.76140046 1
#3 -1.07671647 -4.8747575 0.43706944 1
#4 -1.97701167 1.3015196 0.04390175 2
#5 0.56501325 1.8597720 0.08174124 2
#6 0.70068638 1.7922641 0.74730126 2
#7 -1.39956177 -1.9918904 0.64521918 3
#8 0.27086664 0.3745362 0.61026133 3
#9 0.04282347 3.7360407 0.48696109 3
#10 -0.34262654 0.7933674 0.09824913 3
#I tried:
tapply(dataf$V1, dataf$class, cor, dataf$V2)
#Error FUN(X[[1L]], ...) : incompatible dimensions
tapply(dataf$V1, dataf$class, cor, tapply(dataf$V2, dataf$class))
#Error FUN(X[[1L]], ...) : incompatible dimensions
#But using "by" I obtain:
by(dataf[,c("V1","V2")], dataf$class, cor)
#dataf$class: 1
# V1 V2
#V1 1.00000 0.91777
#V2 0.91777 1.00000
#--------------------------------------------------------------------------------------------------
#dataf$class: 2
# V1 V2
#V1 1.000000 0.987857
#V2 0.987857 1.000000
#--------------------------------------------------------------------------------------------------
#dataf$class: 3
# V1 V2
#V1 1.0000000 0.7318938
#V2 0.7318938 1.0000000
#My interest is on cor(V1,V2)[1,2], so I can take 0.91777, 0.987857 and
0.7318938, but I think that tapply can works better, if I can solve the problem.
Thanks,
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