Gabor Grothendieck wrote:
> On Jan 21, 2008 1:35 PM, Andrew Piskorski <atp@piskorski.com> wrote:
>   
>> On Sun, Jan 20, 2008 at 09:55:40AM -0600, Joe W. Byers wrote:
>>     
>>> I am soliciting your opinions on the different time series objects as to
>>> which you prefer, or which you do not prefer.  I have been using
>>>       
>> I don't know anything about which R time series packages are better
>> (or for what), but I do have a list of some of the ones that exist:
>>
>>    zoo: http://cran.r-project.org/src/contrib/Descriptions/zoo.html
>>    dse: http://www.bank-banque-canada.ca/pgilbert/
>>    its: http://cran.r-project.org/src/contrib/Descriptions/its.html
>>   urca: http://cran.r-project.org/src/contrib/Descriptions/urca.html
>>    ast: http://sirio.stat.unipd.it/index.php?id=libast
>> tseries: http://cran.r-project.org/src/contrib/Descriptions/tseries.html
>>   tsa2: http://www.stat.pitt.edu/stoffer/tsa2/index.html
>>         http://www.amazon.com/Time-Analysis-Its-Applications-Statistics/dp/0387293175/
>> RTisean, tsdyn, and tserieschaos:
>>  http://antonio.fabio.googlepages.com/rprojects
>> And even more via 'label:timeseries' on Google Code:
>>  http://code.google.com/hosting/search?q=label:timeseries&filter=0
>>     
>
> I think many of these are focused on time series functions rather than
> time series representations which seems to be more the topic of
> discussion.
>
>   
The time series representation is the main issue here.  For example, I 
create custom analytics objects of various statistics and/or plot 
capabilities, I want a standard representation of the time series data.  
Another example is that I create a simulation object that I want to pass 
to a valuation object, that will utilize or extend the analytics object 
previous mentioned to provide goodness of fit measure from the 
simulation and individual trajectory statistics or percentile statistics 
in line with the original analytics.  All of these objects require an 
underlying time series representation that is consistent.

> The CRAN Task Views on empirical finance and econometrics have some
> discussion and lists of the time series packages in R.
>
>   
>> And here's my super-short summary of what others have said elsewhere
>> in this thread:
>>
>> - zoo and/or xts are good.
>>     
>
> Maybe that is going a bit far in cursory treatment.
>
> xts
> - what xts is is a subclass of zoo with its own is, as, coredata, print
> and [ methods.
> - it requires use of Date or POSIXct as the index class.  This has
> the advantage that it can make certain assumptions which its
> superclass zoo cannot make due to zoo's greater generality.
> For example, the :: notation (which is roughly a counterpart of the
> window() function in ts and zoo) is made possible by the fact that
> it knows that the index is Date or POSIXct whereas zoo's
> index could be practically anything.  On the other hand, with
> xts you cannot directly model a quarterly series, say, other
> than to embed it into a daily series, say.  However, as xts
> is a zoo subclass you can directly access all zoo functionality
> whenever you want so it would not be a problem to use xts
> to model a daily Date class series and then convert it to yearmon
> and keep going using just zoo at that point.
> - xts has an as.xts.timeSeries method which can convert
> timeSeries objects to xts/zoo.
> - xts is at version 0.0.x and is not ready for wide use (all
> the examples posted here would not work when I tried them)
> but over time xts may gain maturity.  Given the interest shown
> I would expect it might proceed rapidly.
>
> zoo is a mature package with two vignettes (three in the next
> version) that has been around quite a while now and provides
> a general framework for modelling irregularly spaces series.
> A description of zoo can be found in
> library(zoo)
> vignette("zoo")
> vignette("zoo-quickref")
> There are many other packages that use it or add
> infrastructure to it such as xts, quantmod, dyn,
> strucchange, etc.
>
>   
>> - zoo and/or xts basically make ts and tseries obsolete.
>>     
>
> I don't think they make ts obsolete.  zoo (and therefore xts)
> models irregularly spaced series and zoo also has a model for
> irregularly spaced series which having an underlying regularity
> whereas ts is based on strictly regular series.  Of course both
> of zoo's irregular ones include regular ones as a subset but there
> may be some situations where you prefer to model the regularity
> directly.  Also ts is in the core of R and zoo and xts are not.
> I use ts sometimes although I use zoo more.
>
> tseries contains a time series model, irts.  The rest of tseries
> consists of various time series functions and do not depend on irts
> thus tseries as a package is not obsolete.
>
>   
>> - Rmetrics' timeSeries is useful but has certain problems.
>>     
>
> Its main advantages are that many or at least some Rmetrics
> functions use or can use that representation and it supports
> financial centers.
>
> Financial centers is really a property of the index class and not
> necessarily of the time series so one could support this in zoo as
> well by defining an appropriate index class.  e.g. as.xts.timeSeries
>   


I want to thank all of you for you insightful comments and look forward 
to others that are submitted.

Joe


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