leap years (Was: [R] lm and time series)

[Gabor Grothendieck]

The other approach is the pastecs::daystoyears approach where each
year consists of 365.25 days.

Kjetil Brinchmann Halvorsen <kjetil <at> acelerate.com> writes:

: 
: A followup:
: 
: How do people treat dsaily time series, when there is a yearly cycle?
: 
: For the moment I just left out the 29 of February's, but that dsoes'nt look
: really good. Is the only way to include them to use irregular time series?
: 
: Kjetil
: 
: Gabor Grothendieck wrote:
: 
: > 
: >From:   Matthieu Cornec <matthieu.cornec <at> gmail.com>
: > 
: >  
: >
: >>I create a multivariate time series containing NA values (that could
: >>come directly from an imported file,)
: >>I want to compute a linear regression and obtain a time serie for both
: >>residuals and fitted values. I have tried the trick ts.intersect,
: >>without success.
: >>
: >>Could you help me out of this?
: >>####
: >>Example:
: >>
: >>y<-ts(1:10+rnorm(10))
: >>x<-ts(1:10)
: >>datats<-cbind(y,lagx=lag(x))
: >>
: >>Notice the datats could come directly from an imported file, that is
: >>why I did not use ts.intersect(y,lagx=lag(x))
: >>
: >>fit<-lm(y~lagx,data=datats,na.action=na.omit)
: >>
: >>but how do I get a time serie of residuals instead of a vector residuals
(fit)?
: >>######
: >>
: >>Matthieu Cornec
: >>
: >>    
: >>
: >
: >ts is used for regular time series.  Removing NAs, other
: >than at the beginning or end, means its probably best to
: >model it as an irregular time series and so to use an
: >irregular time series package.  Below it is done in zoo.  
: >Also review the comments in my post to your previous question 
: >along these lines and, in particular, be sure you read the zoo vignette 
referenced there which has 15 pages
: of examples
: >of time series manipulations.
: >
: >
: >library(zoo)
: >
: ># set up test data with NAs
: >set.seed(1)
: >x <- zoo(1:10)
: >y <- x + rnorm(10)
: >y[5] <- x[2] <- NA
: >
: ># create multivariate zoo series without NAs
: ># Note: if you want to fill in NAs rather than omit them see ?na.locf
: >z <- na.omit(merge(y, lagx = lag(x, -1)))
: >
: ># run lm
: ># (This also works:   z.lm <- lm(I(y ~ lagx), z)
: ># but the syntax is experimental.)
: >z.lm <- lm(y ~ lagx, as.data.frame(z))
: >
: ># get fitted and resid using fact that their time base is that of z
: >z.fit <- z.resid <- z[,1]
: >z.fit[] <- fitted(z.lm)
: >z.resid[] <- resid(z.lm)
: >
: ># We can just use the zoo series already created.  Its not really
: ># necessary to convert it to ts but if for some reason we want a 
: ># ts series the following creates one.
: ># (This uses facts that we know y starts at 1 and is regularly spaced
: ># and other series have a subset of the time base of y.)
: >ts(coredata(merge(y, x, z.fit, z.resid)))
: >
: >______________________________________________
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: >https://stat.ethz.ch/mailman/listinfo/r-help
: >PLEASE do read the posting guide! http://www.R-project.org/posting-
guide.html
: >
: >
: >
: >  
: >
: