[R] Ordered Multidimensional Arrays

[Whit Armstrong]

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 <pburns at 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
> patrick at 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]]
>>
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>
> ______________________________________________
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