[R] (1) arima.mle implementation; (2) r-newbie forum

Prof Brian D Ripley ripley at stats.ox.ac.uk
Sun Apr 9 20:37:45 CEST 2000

On Sun, 9 Apr 2000, Barry Cooke wrote:

> Has arima.mle (MASS, Ch.15, p.464) been implemented in R?
> [A search through contributed packages and R-FAQ suggests not,
> and I don't think function 'lme' from package 'nlme' would
> accomplish the same sort of thing, although it permits
> correlated errors.  A search of the CRAN site shows this 
> question has been asked some time ago, and it was suggested
> that Paul Gilbert's DSE library might offer comparable 
> functions.  Is this the way to go?]

Look at the on-line V&R `R Complements' for how to do things in MASS in R.
See arima0 in library ts (which is a standard package).

> Using R 1.0.0 for Win9x. Moving to Linux in September :)
> Incidentally, R is great, and so is this forum.  As the user
> base is expanding, it might be a good idea to start a second
> help forum where newbies can discuss "stupid questions" amongst
> ourselves.  I think there are alot more R-related questions out
> there than are currently being asked.  And even now many of
> the questions being posted have as much to do with the use of
> statistics as with the use of R proper.  Having another
> forum (r-newuser? r-statshelp?) might free up core team members
> from having to answer those trivial questions that experienced
> users can easily handle and questions that are only tangentially
> related to R.

We would be very happy for `experienced users' to answer them on r-help.

> [For example I would like to know, but am hesitant to ask:
> 1. How does one interpret the confidence limits computed by
> spec.pgram and automatically plotted by plot.spec?

(pointwise? Sorry, I miss the point here. 
You found package ts, so how did you miss arima0?)

> 2. What is the most elegant way to generate a vector of
> correlated random numbers of arbitrary distribution, mean, 
> variance and correlation structure? (eg. pink noise).]

Well, you can't have arbitrary distribution and covariance structure.
There are theoretical constraints on the correlation between two rv's,
even. For normal distributions, see section 4.5 of BDR (1987) Stochastic
Simulation and choose the method that takes your fancy.

Brian D. Ripley,                  ripley at 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

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