Yearly aggregates and matrices

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))))

--
View this message in context: http://r.789695.n4.nabble.com/Yearly-aggregates-and-matrices-tp3438140p3462564.html
Sent from the R help mailing list archive at Nabble.com.