Dear R experts.
I might be missing something obvious. I have been trying to fix this problem
for some weeks. Please help.
#data
ped <- c(rep(1, 4), rep(2, 3), rep(3, 3))
y <- rnorm(10, 8, 2)
# variable set 1
M1a <- sample (c(1, 2,3), 10, replace= T)
M1b <- sample (c(1, 2,3), 10, replace= T)
M1aP1 <- sample (c(1, 2,3), 10, replace= T)
M1bP2 <- sample (c(1, 2,3), 10, replace= T)
# variable set 2
M2a <- sample (c(1, 2,3), 10, replace= T)
M2b <- sample (c(1, 2,3), 10, replace= T)
M2aP1 <- sample (c(1, 2,3), 10, replace= T)
M2bP2 <- sample (c(1, 2,3), 10, replace= T)
# variable set 3
M3a <- sample (c(1, 2,3), 10, replace= T)
M3b <- sample (c(1, 2,3), 10, replace= T)
M3aP1 <- sample (c(1, 2,3), 10, replace= T)
M3bP2 <- sample (c(1, 2,3), 10, replace= T)
mydf <- data.frame (ped, M1a,M1b,M1aP1,M1bP2, M2a,M2b,M2aP1,M2bP2,
M3a,M3b,M3aP1,M3bP2, y)
# functions and further calculations
mmat <- matrix
(c("M1a","M2a","M3a","M1b","M2b","M3b","M1aP1","M2aP1","M3aP1",
"M1bP2","M2bP2","M3bP2"), ncol = 4)
# first function
myfun <- function(x) {
x<- as.vector(x)
ot1 <- ifelse(mydf[x[1]] == mydf[x[3]], 1, -1)
ot2 <- ifelse(mydf[x[2]] == mydf[x[4]], 1, -1)
qt <- ot1 + ot2
return(qt)
}
qt <- apply(mmat, 1, myfun)
ydv <- c((y - mean(y))^2)
qtd <- data.frame(ped, ydv, qt)
# second function
myfun2 <- function(dataframe) {
vydv <- sum(ydv)*0.25
sumD <- sum(ydv * qt)
Rt <- vydv / sumD
return(Rt)
}
# using plyr
require(plyr)
dfsumd1 <- ddply(mydf,.(mydf$ped),myfun2)
Here are 2 issues:
(1) The output just one, I need the output for all three set of variables
(as listed above)
(2) all three values of dfsumd is returning to same for all level of ped:
1,2, 3
Means that the function is applied to whole dataset but only replicated in
output !!!
I tried with plyr not being lazy but due to my limited R knowledge, If you
have a different suggestion, you are welcome too.
Thank you in advance...
Maya
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