**Subject: **RE: time series in R

**From: **Prof Brian Ripley (*ripley@stats.ox.ac.uk*)

**Date: **Tue 20 Jul 1999 - 21:10:06 EST

**Next message:**Adrian Trapletti: "Re: time series in R"**Previous message:**Peter Dalgaard BSA: "Re: 0.65/AIX"**Maybe in reply to:**Prof Brian D Ripley: "time series in R"**Next in thread:**Martyn Plummer: "RE: time series in R"**Maybe reply:**Prof Brian Ripley: "RE: time series in R"

Message-Id: <199907201110.MAA04887@toucan.stats.ox.ac.uk>

*> Date: Tue, 20 Jul 1999 11:17:51 +0200 (CEST)
*

*> From: Martyn Plummer <plummer@iarc.fr>
*

*> To: Prof Brian D Ripley <ripley@stats.ox.ac.uk>
*

*> Subject: RE: time series in R
*

*>
*

*> On 19-Jul-99 Prof Brian D Ripley wrote:
*

*> > Time Series functions in R
*

*> > ==========================
*

*> > If Martyn and Adrian are agreeable, I will start a library(ts) in the
*

*> > 0.65 version. I will put in this:
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*> >
*

*> > the ts class and methods (maybe in due course these should be removed
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*> > from the base package?)
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*>
*

*> Some of the ts class stuff is implemented in the C code of the base
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*> library. I'm not sure you can separate this.
*

Rather, in the C core of R (the base package has no C code). I was not

intended to separate that. My aim was merely to allow some code to be

re-written without losing backwards compatibility, yet. For example,

print.ts does not do well with multiple series (and it breaks the

cardinal rule of a print method returning its first argument unchanged).

*> I also suggested an "na.omit" method for time series - which would be
*

*> used by many of the time series functions. Martin has made na.omit()
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*> and na.fail() generic so this is possible now.
*

Good. What do you want na.omit.ts to do?

*> > filter
*

*>
*

*> I think there is some functional overlap between filter() and convolve(),
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*> which now has a type="filter" option. I'm not sure convolve() needs this
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*> if there is a filter() function.
*

I'll take a look.

*>
*

*> > acf from bats, augmented by ideas from tseries.
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*>
*

*> I updated acf() in bats_0.1-3.tar.gz (now on CRAN) to use FFT instead,
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*> after seeing its rather embarrassing performance.
*

I have that. However, I am having a number of problems with it,

for example that pacf does not work, and acf does not work correctly

for multiple series.

*> library(bats)
*

*> data(presidents)
*

*> acf(presidents, type="partial")
*

Error: Object "xb" not found

OK, fix that:

*> acf(presidents, type="partial")
*

Error: NA/NaN/Inf in foreign function call (arg 1)

[The NA handling needs to be sorted out.]

A little later:

var0 <- diag(acf[1, , ], nrow = nser)

is wrong: it gives a matrix and multivariate acfs fail. I used

var0 <- if(nser > 1) diag(acf[1, , ]) else acf[1,1,1]

I think I will special-case the univariate code here.

*> > spectrum, spec.pgram from bats (after looking at tseries hard)
*

*>
*

*> Adrian's spectrum() function allows a wider range of kernel smoothers
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*> and it would be nice to keep this. Since spectrum() is just a wrapper
*

*> function anyway, it should be possible to do this, while keeping the
*

*> S-PLUS compatible interface.
*

Yes, I intend to look at that. For now, though, your code is not

giving the same results as S-PLUS, and I need to fix up at least the

confidence interval calculations. (I think I know exactly how it

is done in S-PLUS: it uses Bloomfield's code.) I believe that padding

needs to be optional.

*> > ar.yw from bats (although that probably needs to be moved to
*

*> > C/Fortran, and I may special-case the univariate case to use code I
*

*> > have for that).
*

*>
*

*> I haven't tried very hard to make my code efficient, as you can see,
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*> concentrating instead on getting something that works like the S-PLUS
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*> version. Much of the work involved trying to get the same answer as
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*> S-PLUS, and when that wasn't possible, trying to work out what S-PLUS
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*> was doing wrong (see the COMPAT file).
*

*>
*

*> I think the multivariate version would be harder to implement in C.
*

I agree, but maybe it should be done.

*> I will see if I can speed the R code up.
*

*>
*

*> I have been looking at Burg's algorithm and I think I can implement
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*> this now, if you want.
*

Yes, please (even though I think it is in principle a bad idea).

*> > As the feature-freeze for 0.65 is probably about 2-3 weeks away, we
*

*> > ought to concentrate on getting the basic stuff (bats-like) in first.
*

Looking at where I am, that looks feasible

Brian

-- Brian D. Ripley, ripley@stats.ox.ac.uk Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272860 (secr) Oxford OX1 3TG, UK Fax: +44 1865 272595-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel 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-devel-request@stat.math.ethz.ch _._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._._

**Next message:**Adrian Trapletti: "Re: time series in R"**Previous message:**Peter Dalgaard BSA: "Re: 0.65/AIX"**Maybe in reply to:**Prof Brian D Ripley: "time series in R"**Next in thread:**Martyn Plummer: "RE: time series in R"**Maybe reply:**Prof Brian Ripley: "RE: time series in R"

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