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.
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