[R] Irregular time series

[Philippe Grosjean]

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.
Best,

Philippe Grosjean

...........]<(({?<...............<?}))><...............................
 ) ) ) ) )
( ( ( ( (       Dr. Philippe Grosjean
 ) ) ) ) )
( ( ( ( (       LOV, UMR 7093
 ) ) ) ) )      Station Zoologique
( ( ( ( (       Observatoire Oceanologique
 ) ) ) ) )      BP 28
( ( ( ( (       06234 Villefranche sur mer cedex
 ) ) ) ) )      France
( ( ( ( (
 ) ) ) ) )      tel: +33.4.93.76.38.16, fax: +33.4.93.76.38.34
( ( ( ( (
 ) ) ) ) )      e-mail: phgrosjean at sciviews.org
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 ) ) ) ) )
.......................................................................



-----Original Message-----
From: r-help-admin at stat.math.ethz.ch
[mailto:r-help-admin at stat.math.ethz.ch]On Behalf Of Damon Wischik
Sent: lundi 27 janvier 2003 10:42
To: r-help at stat.math.ethz.ch
Subject: [R] Irregular time series



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:

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)
  }

but it is very slow (for a data frame of 102,000 lines, converted into a
time series of 130,000 points). Is there a better way?

Damon Wischik.

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