Hello,
I'm a R newcomer and I'm wondering the kind of data structure that would
best fit to my problem:
my data are equities (stocks) : so I have a time serie (say 1 year of weekly
data), and a bunch of qualitative + quantitative variables :
the sector of the stock (biotech/finance...), the geographical region, the
name, ISIN code, P/E ratios, whatever...

The data.frame is perfect for the qualitative variables : a row is a stock,
a column is a variable .
But where can I store the time serie? If I put each weekly data in a column
of the data frame
, I'm not sure that it's the best structure when I will want to test
some models on these
(regressions/arma/whatever).
I would prefer to have a new data frame, where each column is a stock, each
row a date, to do the regressions (across time more easily)

So I would end up with 2 data frames, one of each transposed... No good,
probably.

I thought of a set of 2 objects : 1 data frame (for the qualitative
variables), and one list of time series, in the same order, with the risk of

forgetting to subset one objet and not the other, etc...

Do you happen to have the same kind of problem?
Is there something equivalent in R as the matlab 'structures' ? (kinda R
data frame, where you can store multi-dimensional objects in a column)

Many thanks in advance.

Regards

Roolio

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