Hi. I have a question concerning the easiest way to index a time series object holding some stock quotes. An example:> ibm <- get.hist.quote("IBM",start="2000-01-01")My question is:- Suppose I want to know the stock quotes on 2000-01-03. Which is the easiest way to index the "ibm" time series object to get them? I got what I wanted using:>window(ibm,start=julian(as.POSIXct("2000-01-03")),end=julian(as.POSIXct("2000-01-03"))) But I'm sure there is a much better way to get it! In summary, my problem is to find the easiest way to convert from my "natural" way of thinking on the quotes (which is date-based) into the indexing schema of time series objects, which by looking at the code of "get.hist.quote" is based on the conversion into the number of days (using "julian") from an origin. Thank you for any help. Luis -- Luis Torgo FEP/LIACC, University of Porto Phone : (+351) 22 607 88 30 Machine Learning Group Fax : (+351) 22 600 36 54 R. Campo Alegre, 823 email : ltorgo at liacc.up.pt 4150 PORTO - PORTUGAL WWW : http://www.liacc.up.pt/~ltorgo -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._
On Fri, Jun 28, 2002 at 10:18:42AM +0100, Luis Torgo wrote:> > ibm <- get.hist.quote("IBM",start="2000-01-01")[...]> window(ibm,start=julian(as.POSIXct("2000-01-03")),end=julian(as.POSIXct("2000-01-03")))[...]> In summary, my problem is to find the easiest way to convert from my > "natural" way of thinking on the quotes (which is date-based) into the > indexing schema of time series objects, which by looking at the code of > "get.hist.quote" is based on the conversion into the number of days (using > "julian") from an origin.I don't think there is -- ts() cannot deal that well with "business-daily" data. It is intended for monthly or quarterly data with regular increments, or frequency. Dealing with daily data with weekends and holidays is much harder. Adrian's solution of converting to Julian and padding with NaN for non-business days is probably as good as it gets. Dirk -- Good judgement comes from experience; experience comes from bad judgement. -- Fred Brooks -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To: r-help-request at stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._