As a follow up on this post, I am trying to slightly adjust the solution
kindly provided by Gabor. However, I am getting some results that I do not
understand. Example:
# devel version of zoo
install.packages("zoo", repos = "http://r-forge.r-project.org";)
library(zoo)
DF1 = data.frame(read.table(textConnection(" B C D E F G
8025 1995 0 4 1 2
8025 1997 1 1 3 4
8026 1995 0 7 0 0
8026 1996 1 2 3 0
8026 1997 1 2 3 1
8026 1998 6 0 0 4
8026 1999 3 7 0 3
8027 1997 1 2 3 9
8027 1998 1 2 3 1
8027 1999 6 0 0 2
8028 1999 3 7 0 0
8029 1995 0 2 3 3
8029 1998 1 2 3 2
8029 1999 6 0 0 1"),head=TRUE,stringsAsFactors=FALSE))
a <- read.zoo(DF1, split = 1, index = 2, FUN = identity)
sum.na <- function(x) if (any(!is.na(x))) sum(x, na.rm = TRUE) else NA
b <- rollapply(a, 3, sum.na, align = "right", partial = TRUE)
newDF <- lapply(1:nrow(b), function(i)
prop.table(na.omit(matrix(b[i,], nc = 4, byrow = TRUE,
dimnames = list(unique(DF1$B), names(DF1)[-1:-2]))), 1))
names(newDF) <- time(a)
c<-lapply(newDF, function(mat) tcrossprod(mat / sqrt(rowSums(mat^2))))
Now I would like the elements e in c to be equal to 1-e. However,
c<-lapply(newDF, function(mat) 1 - tcrossprod(mat / sqrt(rowSums(mat^2))))
gives a value of 2.220446e-16 for as.data.frame(c['1999'])[2,2] instead of
0
What am I doing wrong here? Thanks a lot!
> First we use read.zoo to reform DF into a multivariate time series and
> use rollapply (where we have used the devel version of zoo since it
> supports the partial= argument on rollapply). We then reform each
> resulting row into a matrix converting each row of each matrix to
> proportions. Finally we form the desired scaled cross product.
>
> # devel version of zoo
> install.packages("zoo", repos = "http://r-forge.r-project.org";)
> library(zoo)
>
> z <- read.zoo(DF, split = 2, index = 3, FUN = identity)
>
> sum.na <- function(x) if (any(!is.na(x))) sum(x, na.rm = TRUE) else NA
> r <- rollapply(z, 3, sum.na, align = "right", partial = TRUE)
>
> newDF <- lapply(1:nrow(r), function(i)
> prop.table(na.omit(matrix(r[i,], nc = 4, byrow = TRUE,
> dimnames = list(unique(DF$B), names(DF)[-2:-3]))[, -1]),
> 1))
> names(newDF) <- time(z)
>
> lapply(newDF, function(mat) tcrossprod(mat / sqrt(rowSums(mat^2))))
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