Hello,
Instead of try(cor.test) you could try(return_cor).
Also, isn't there a bug in return_cor? See the commented line below.
return_cor = function(x, y, tresh = 0.05) {
z = cor.test(x,y)
if(z[[3]] < tresh) {
return(z[[4]]) # not z[[5]], always zero
} else {
return(NA)
}
}
cor_withN <- function(...) {
res <- try(return_cor(...), silent=TRUE)
ifelse(class(res)=="try-error", NA, res)
}
cor_withN(1:10, 1:10 + rnorm(10))
cor_withN(1:2, 1:2 + rnorm(2))
Hope this helps,
Rui Barradas
Em 22-02-2013 15:04, Jonsson escreveu:> I am using the code below to calculate the correlation map between two
> datasets. This code worked fine.
>
> dir1 <- list.files("D:thly", "*.bin",
full.names = TRUE)
> dir2 <- list.files("D:002", "*.envi",
full.names = TRUE)
> file_tot <- array(dim = c(1440, 720, 11, 2))
> for(i in 1:length(dir1)) {
> file_tot[, , i, 1] <- readBin(dir1[i], numeric(), size = 4,
> n = 1440 * 720, signed = T)
> file_tot[, , i, 2] <- readBin(dir2[i], numeric(), size = 4,
> n = 1440 * 720, signed = T)
> }
> resultscor<-apply(file_tot,c(1,2),function(x){cor(x[,1],x[,2],use
> "na.or.complete")})
>
> I would like to calculate the correlation only when the `P-value is lower
> than 0.05`. so this function bellow will do the job:
>
> return_cor = function(x, y) {
> z = cor.test(x,y)
> if(z[[3]] < 0.05) {
> return(z[[5]])
> } else {
> return(NA)
> }
> }
>
> However I got this error(as some pairs of my data are less then 3):
>
> Error in cor.test.default(x, y) : not enough finite
> observations
>
> in order to avoid this error and return NA when there are less than 3
> pairs,this function does the job:
>
> cor_withN <- function(...) {
> res <- try(cor.test(...)$estimate, silent=TRUE)
> ifelse(class(res)=="try-error", NA, res)
> }
> Both functions worked perfectly.How can we merge both functions into one
> function so we calculate correlation when P value is (certain value,
> threshold) and also do the calculations even if there are less than 3
pairs.
>
>
>
>
> --
> View this message in context:
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>
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