R help - Jan 2002 - multivariate simulation

To whom it may concern,

I try to simulate a non-normal multivariate distribution. The MASS package
allows by mean of "mvrnorm" command to perform a multivariate normal
simulation. Is there an equivalent command for an arbitrary multivariate
distribution available in the R-language?

Thank you in advance.

Bernard Colin


Colin Bernard
Professeur titulaire
D?partement de Math?matiques et d'Informatique
Facult? des Sciences
Universit? de Sherbrooke
SHERBROOKE J1K-2R1 (Qu?bec)
Canada
Tel : (819)821-8000 poste 2012
Fax :(819)821-8200
e-mail : bernard.colin at dmi.usherb.ca

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On Wed, 23 Jan 2002, Bernard Colin wrote:
> To whom it may concern,
>
> I try to simulate a non-normal multivariate distribution. The MASS package
> allows by mean of "mvrnorm" command to perform a multivariate
normal
> simulation. Is there an equivalent command for an arbitrary multivariate
> distribution available in the R-language?
There is no equivalent command to sample from an arbitary *univariate*
distribution either!  There are no general algorithmic methods even in the
univariate case, although inversion comes closest.

-- 
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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On Wed, 23 Jan 2002, Bernard Colin wrote:
> To whom it may concern,
>
> I try to simulate a non-normal multivariate distribution. The MASS package
> allows by mean of "mvrnorm" command to perform a multivariate
normal
> simulation. Is there an equivalent command for an arbitrary multivariate
> distribution available in the R-language?
>
No. An `arbitrary multivariate distribution' covers a whole lot of
possibilities.

It would be fairly easy to write a function that linearly transformed an
arbitrary starting distribution to have arbitrary mean and variance in the
same way that mvrnorm() does, but that is usually not desirable.

It is unusual (? unique) to the Normal that this procedure produces a
random vector that is marginally and conditionally Normal.  An analogous
mvrgamma would produce variables that are not Gamma distributed and an
mvrpois wouldn't even produce integers.

There are many other ways of producing multivariate versions of univariate
distributions and most of them are `natural' for only a few cases.

If you could be more specific about what you want someone might be able to
help, but most of these methods aren't programmed in R. Jim Lindsey's
packages have a few.

	-thomas

Thomas Lumley			Asst. Professor, Biostatistics
tlumley at u.washington.edu	University of Washington, Seattle

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Hi All,

If I have a factor f:

A B C B C A C B A A B ....

and I would like to generate a factor to indicate the trial number
as a function of condition: e.g.

1 1 1 2 2 2 3 3 3 4 4 ...

how might I attack this in R?

thanks,

Brad Buchsbaum

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Brad Buchsbaum wrote:
> 
> Hi All,
> 
> If I have a factor f:
> 
> A B C B C A C B A A B ....
> 
> and I would like to generate a factor to indicate the trial number
> as a function of condition: e.g.
> 
> 1 1 1 2 2 2 3 3 3 4 4 ...
> 
> how might I attack this in R?
What about something like
  as.factor(outer(rep(1, 3), 1:4))

Uwe
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On Wednesday 23 January 2002 02:11 pm, Uwe Ligges wrote:
> Brad Buchsbaum wrote:
> > Hi All,
> >
> > If I have a factor f:
> >
> > A B C B C A C B A A B ....
> >
> > and I would like to generate a factor to indicate the trial number
> > as a function of condition: e.g.
> >
> > 1 1 1 2 2 2 3 3 3 4 4 ...
> >
> > how might I attack this in R?
>
> What about something like
>   as.factor(outer(rep(1, 3), 1:4))
>
> Uwe
I should have mentioned that the condtions A, B, C vary randomly,
so I have to perform some operation on the existing factor "f".

Brad B.

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When you say that a distribution is normal, you can tell very
specific properties, but when you say thatis "not normal"
there is an infinite range of possibilities (just as when you
say that a function is non-linear...). You must investigate
your data and come up with some alternative distributions
that you can test as alternative hypothesis. Perhaps the
book Hilborn and Mangel 1997 The ecological detective, confronting
models with data (princeon Univ. Press) might be useful
for you.

Agus

Dr. Agustin Lobo
Instituto de Ciencias de la Tierra (CSIC)
Lluis Sole Sabaris s/n
08028 Barcelona SPAIN
tel 34 93409 5410
fax 34 93411 0012
alobo at ija.csic.es


On Wed, 23 Jan 2002, Bernard Colin wrote:
> To whom it may concern,
> 
> I try to simulate a non-normal multivariate distribution. The MASS package
> allows by mean of "mvrnorm" command to perform a multivariate
normal
> simulation. Is there an equivalent command for an arbitrary multivariate
> distribution available in the R-language?
> 
> Thank you in advance.
> 
> Bernard Colin
> 
> 
> Colin Bernard
> Professeur titulaire
> Département de Mathématiques et d'Informatique
> Faculté des Sciences
> Université de Sherbrooke
> SHERBROOKE J1K-2R1 (Québec)
> Canada
> Tel : (819)821-8000 poste 2012
> Fax :(819)821-8200
> e-mail : bernard.colin at dmi.usherb.ca
> 
>
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> r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html
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>
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> 
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