Create matrices for time series

Hi list, I would like to use the following data.frame to generate matrices
over a 3 year moving window:

DF = data.frame(read.table(textConnection(" ?A ?B ?C
80 ?8025 ?1995
80 ?8026 ?1995
80 ?8029 ?1995
81 ?8026 ?1996
82 ?8025 ?1997
82 ?8026 ?1997
83 ?8025 ?1997
83 ?8027 ?1997
84 ?8026 ?1999
84 ?8027 ?1999
85 ?8028 ?1995
85 ?8029 ?1998"),head=TRUE,stringsAsFactors=FALSE))

Function to be applied: t(as.matrix(table(DF[,1:2]))) %*%
as.matrix(table(DF[,1:2]))

I tried this without success:
n<-rollapply(DF, width = 3, FUN = t(as.matrix(table(DF[,1:2]))) %*%
as.matrix(table(DF[,1:2])), align = "right")

Try this:

Lines <- "  A  B  C
80  8025  1995
80  8026  1995
80  8029  1995
81  8026  1996
82  8025  1997
82  8026  1997
83  8025  1997
83  8027  1997
84  8026  1999
84  8027  1999
85  8028  1995
85  8029  1998"

DF <- read.table(textConnection(Lines), header = TRUE)

f <- function(y) crossprod(table(DF[DF$C %in% y, 1:2]))
years <- sort(unique(DF$C))
e <- as.data.frame(embed(years, 3))
lapply(split(e, e[, 1]), f)

Statistics & Software Consulting
GKX Group, GKX Associates Inc.
tel: 1-877-GKX-GROUP
email: ggrothendieck at gmail.com

Thanks a lot!

Given the calculations below, I would like to generate a data.frame in which
the value of case 8029 (i) in 1998 = sum (element c(i,j) * element
final1(1,j) * 1st eigenvalue 1998 * element final2 (i,j)) * (1/sum
final2(i)) in which j are all other cases in year 1998 and i IS NOT j?
so for 8029 in 1998 = (0.9072184 * -0.5093407 * 3.64178798 * 0 + 0.8733873 *
-0.4763885 * 3.64178798 * 1 + 0.9058216 * -0.5072112 * 3.64178798 * 1) *
(1/3) = -1.06281276

Using this formula, I would like to generate a list per year (1997 - 1999)
with all unique cases (1998 = 8025, 8026, 8027, 8029) in that year and the
outcome of the formula.

I've been trying to run this formula, but I am having a hard time connecting
each element to each other element. Could anyone please help me? Thanks in
advance!
 
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))))
d <- lapply(c, function(x) eigen(x, symmetric = TRUE, only.values = FALSE,
EISPACK = FALSE))


DF2 = data.frame(read.table(textConnection("  A  B  C
80  8025  1995
80  8026  1995
80  8029  1995
81  8026  1996
82  8025  1997
82  8026  1997
83  8025  1997
83  8027  1997
90  8026  1998
90  8027  1998
90  8029  1998
84  8026  1999
84  8027  1999
85  8028  1999
85  8029  1999"),head=TRUE,stringsAsFactors=FALSE))

e <- function(y) crossprod(table(DF2[DF2$C %in% y, 1:2])) 
years <- sort(unique(DF2$C)) 
f <- as.data.frame(embed(years, 3)) 
g<-lapply(split(f, f[, 1]), e)
library(sna)
h<-event2dichot(g, method="absolute", thresh=0.99)


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