[R] Irregular time series
Damon Wischik
djw1005 at cam.ac.uk
Tue Jan 28 11:25:05 CET 2003
>> I have an irregular time series, stored as a data frame, in the form
>> Time Bytes
>> 57213.191 20
>> 57213.193 20
>> 57213.300 23
>> ... ...
>> How should I convert this into a regularly-spaced time series?
>> I have in mind to divide time into equal-sized intervals, and sum the
>> number of Bytes in each interval. I tried this: ...
Philippe Grosjean wrote:
> You will find all required tools in the PASTECS library, including
> regul.screen() and regul.adj() to determine best time step in the regular
> series (with a maximum number of observations matching those in the initial
> irregular series), and four different regulation methods: regconst(),
> reglin(), regspline() and regarea(), all available in the more general
> regul() function.
Thank you for the link. As I understand them, none of those regulation
methods achieve what I want. I want to divide time into equal-sized
intervals, and sum the number of bytes arriving in each interval. I do not
want any sort of interpolation of existing values. Those four regulation
methods are all different types of interpolation, if I understand
correctly.
My dataset represents a point arrival process, not a sample of a
continuous process; I want to turn the continuous-time point arrival
process into a discrete-time point arrival process. I am looking for a
function which has the same effect as, but is faster than, this:
> its.to.ts <- function(times,values,delta=1) {
> m <- min(times)
> M <- max(times)
> mm <- delta*floor(m/delta)
> MM <- delta*ceiling(M/delta)
> cuts <- seq(from=mm,to=MM,by=delta)
> nullvals <- rep(0,length(cuts)-1)
> nulltimes <- cuts[-1]-delta/2
> time.factor <- cut(c(times,nulltimes),cuts,labels=FALSE)
> dd <- aggregate(c(values,nullvals),by=list(time=time.factor),sum)
> ts(data=dd$x,start=mm,deltat=delta)
> }
Damon Wischik.
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