Please suggest a way out to the following problem.
I have a T by n data matrix (say Y) where coulmns are time series of length
T.
To do some analysis in WinBUGS I need to construct my data as follows.
yy<-rep(Y,k) ## this will be a vector
Yk<-array(yy,dim=c(T,n,k)) ## data array
Here the definition of dim indices is
first index: T rows
second index: n columns
third index: for kth T by n array
EXAMPLE
T=3
n=2
k=2
Y<-matrix(c(1,2,3,4,5,6), ncol=n) ## my data matrix
yy<-rep(Y,k)
Yk<-array(yy,dim=c(T,n,k))
Yk # this produces the following R output.
, , 1
[,1] [,2]
[1,] 1 4
[2,] 2 5
[3,] 3 6
, , 2
[,1] [,2]
[1,] 1 4
[2,] 2 5
[3,] 3 6
That is, I have copied the orignal data k=2 times. WinBUGS will be supplied
the following data
d<-list(Yk=Yk, T=T,n=n,k=k).
Now in WinBUGS I have to define a multivariate stochastic node as as follows
e[i,1:n,kk]~dmnorm( , ) ## i= 1,2,...,T ; kk = 1,2,...,k
But Winbugs accepts only something like
e[ , , 1:n]~dmnorm( , ).
That is "1:n" has to be given at the leftmost position.
This means that I need to change the definition of dim indices in R as
follows.
first index: for kth T by n array
second index: T rows
third index: n columns.
Specifically, I want the above output as
1, ,
[,1] [,2]
[1,] 1 4
[2,] 2 5
[3,] 3 6
2, ,
[,1] [,2]
[1,] 1 4
[2,] 2 5
[3,] 3 6
I would appriciate any help in this regard.
Khurram Nadeem
PhD Student
Department of Math. & Stat. Sciences
University of Alberta
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