Convert a matrix back to xts

Question

I have a matrix which represents the eigenvalues of a bunch of correlation matrices over time.

My matrix has a column with the time referenced in it but it's not a time series or an xts object as far as I can tell.

Ultimately I wish to convert this matrix into a format be it data frame or xts object which allows me to plot the N largest eigenvalues over time.

How can I convert this matrix into such a format, I guess XTS is preferable since it is a time series representation?

I have tried the following but I can't get it to work:

time.index <- as.POSIXct(colnames(eigen))
eigenXTS <- as.xts(eigen, order.by = time.index)

but I got an error back referring to

Error in xts(x, order.by = order.by, frequency = frequency, ...) : 
  NROW(x) must match length(order.by)

My data looks as follows:

> class(eigen)
[1] "matrix"

> str(eigen)
 num [1:12, 1:1334] 4.461 2.292 2.216 1.425 0.839 ...
 - attr(*, "dimnames")=List of 2
  ..$ : NULL
  ..$ : chr [1:1334] "2017-01-20 18:45:00" "2017-01-20 19:00:00" "2017-01-20 19:15:00" "2017-01-20 19:30:00" ...

> dim(eigen)
[1]   12 1334

> eigen[1:4,1:4]
     2017-01-20 18:45:00 2017-01-20 19:00:00 2017-01-20 19:15:00 2017-01-20 19:30:00
[1,]            4.461059            4.774866            4.658013            4.841987
[2,]            2.291520            2.330239            2.101630            2.145122
[3,]            2.215749            2.183941            1.935904            1.861954
[4,]            1.424662            1.277794            1.750168            1.762004

Can anyone point me in the direction of how to best approach solving this problem?

Answer 1

I think you need to transpose the matrix and convert to data.frame before converting it to xts so you can have rows as records (observations) and columns as variables.

> dput(eigen)
structure(list(`2017-01-20 18:45:00` = c("4.461059", "2.291520", 
"2.215749", "1.424662"), `2017-01-20 19:00:00` = c("4.774866", 
"2.330239", "2.183941", "1.277794"), `2017-01-20 19:15:00` = c("4.658013", 
"2.101630", "1.935904", "1.750168"), `2017-01-20 19:30:00` = c("4.841987", 
"2.145122", "1.861954", "1.762004")), .Names = c("2017-01-20 18:45:00", 
"2017-01-20 19:00:00", "2017-01-20 19:15:00", "2017-01-20 19:30:00"
), row.names = c(NA, 4L), class = "data.frame")

> eigen <- as.data.frame(t(eigen))
                          V1       V2       V3       V4
2017-01-20 18:45:00 4.461059 2.291520 2.215749 1.424662
2017-01-20 19:00:00 4.774866 2.330239 2.183941 1.277794
2017-01-20 19:15:00 4.658013 2.101630 1.935904 1.750168
2017-01-20 19:30:00 4.841987 2.145122 1.861954 1.762004

> xts_eigen <- xts::xts(eigen,order.by = as.POSIXct(rownames(eigen)))
                          V1       V2       V3       V4
2017-01-20 18:45:00 4.461059 2.291520 2.215749 1.424662
2017-01-20 19:00:00 4.774866 2.330239 2.183941 1.277794
2017-01-20 19:15:00 4.658013 2.101630 1.935904 1.750168
2017-01-20 19:30:00 4.841987 2.145122 1.861954 1.762004

> class(xts_eigen)
[1] "xts" "zoo"

Answer 2

as.xts expects the rownames of the matrix to be the timestamps. In your case, the colnames of eigen contain the timestamps. Therefore, you need to transpose eigen before calling as.xts .

xeigen <- as.xts(t(eigen))
xeigen
#                         [,1]     [,2]     [,3]     [,4]
# 2017-01-20 18:45:00 4.461059 2.291520 2.215749 1.424662
# 2017-01-20 19:00:00 4.774866 2.330239 2.183941 1.277794
# 2017-01-20 19:15:00 4.658013 2.101630 1.935904 1.750168
# 2017-01-20 19:30:00 4.841987 2.145122 1.861954 1.762004

Since an xts object is just a matrix with a time index, there's no need to coerce your matrix to a data.frame. Doing that would mean as.xts would have to coerce it back to a matrix.