I take a similar approach by storing my vcv's in a list w/ the date stored as a character vector "%y-%m-%d" as the list names. That way you can easily grab the vcv you need by casting your date to a string and using it to index the list.
not sure if that will work for you. hth, Whit On Tue, Dec 23, 2008 at 3:08 PM, Patrick Burns <pbu...@pburns.seanet.com> wrote: > The old fashioned solution is to have the N x N x T > array and use character strings of the dates as the > dimnames on the third dimension. > > Is there something you think you need to do that is > hard with such a setup? > > > Patrick Burns > patr...@burns-stat.com > +44 (0)20 8525 0696 > http://www.burns-stat.com > (home of S Poetry and "A Guide for the Unwilling S User") > > Derek Schaeffer wrote: >> >> Hi, >> I am inquiring as to what are the best practices with respect to storing >> and >> manipulating ordered multi-dimensional arrays. For example, suppose I >> have >> a sequence of time-varying covariance matrices of asset returns. The data >> is ordered, but the ordering is not necessarily regular (e.g. daily data >> omitting weekends and holidays, etc.). The data array is say, N x N x T. >> For example, the first two elements may look as follows: >> >> >>> >>> *result$covariance[,,1:2] >>> >> >> , , 1* >> * [,1] [,2] [,3] [,4] >> [1,] 1.511137e-06 1.918668e-06 1.201553e-06 3.205271e-06 >> [2,] 1.918668e-06 7.488916e-06 6.593317e-06 1.203421e-05 >> [3,] 1.201553e-06 6.593317e-06 1.305861e-05 2.132272e-05 >> [4,] 3.205271e-06 1.203421e-05 2.132272e-05 4.571225e-05* >> *, , 2* >> * [,1] [,2] [,3] [,4] >> [1,] 1.500858e-06 1.905574e-06 1.193412e-06 3.183290e-06 >> [2,] 1.905574e-06 7.444871e-06 6.555459e-06 1.195876e-05 >> [3,] 1.193412e-06 6.555459e-06 1.297075e-05 2.117777e-05 >> [4,] 3.183290e-06 1.195876e-05 2.117777e-05 4.551706e-05* >> >> I would like to be able to partition this sequence of matrices by date and >> by individual element. Partitioning by individual elements is trivial; >> however, partitioning by time stamp is not (especially if the partitioned >> data set must be carried through a number of downstream calculations). I >> could carry the data in a list complete with a date vector and the data >> array, and partition the list as I go, but this seems somewhat clunky. >> Any >> ideas? A "zoo"-like package capable of handling multidimensional arrays >> would be optimal, but I don't believe this exists. >> >> Thanks, >> Derek >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> >> >> > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
