Dear all,
 
Am I right in understanding you cannot directly apply functions such as
loess() (filter() as well ?) to zoo objects and you need to use the
rollapply/rollmean functions instead?
 
For example:
 
library("tseries")
DJ<- get.hist.quote("^DJI", start = "1990-01-01", quote = "Close")
DJret<-diff(log(DJ))
 
# the
 
loess(DJret, time(DJret)) 
 
does not work(?). What am I understanding  wrong? I found a reply by
Achim on a similar issue.
 
http://finzi.psych.upenn.edu/R/Rhelp02a/archive/88599.html
 
Is Achim's answer all there is to it?
 
I.e., my problem is a little bit  more general: 
 
Say I want to produce fits and then forecasts on a time series (zoo
mostly) using a non-zoo routine which "understands" ts or timeSeries
objects (or simple vectors).  Do I always have to "translate" zoo
objects to vectors or to ts/simeSeries ones, run the routines and then
put back the zoo attribute with the appropriate dates so as to produce
correct time-series plots (with dates etc, especially correct dates
alligned to the forecast period - which could be postsample)?  
 
Is there an easier way to shift between zoo-ts/timeSeries objects and
produce plots statistical analysis that will have the dates correctly
aligned on (to account for example for irregularly sampled sequences
such as stock prices with non-trading days etc. etc.)?
 
Thanks in advance,
Costas
 
 

P Think before you print.

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