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extension of rnormp package
3 messages · Iwona Szydłowska, Brian Ripley, Elio Mineo
On Mon, 23 Jul 2007, Iwona Szyd?owska wrote:
Hello,
I would like to ask You, how to generate random numbers from an exponential power family with a shape parameter p less than 1(p->0). I found the rnormp package, which can generate numbers from this distribution, but only for parameter less or equal 1.
It seems you mean package 'normalp', and that the package author believes that the exponential power distribution is only defined for p >= 1 (although that is not on the help page). Other authors believe it is defined by a relationship to the gamma for all p > 0. So all you need to do is to change the condition from p < 1 to p <= 0 in rnormp and friends. However, the algorithms used are not adequate for large or small p. We know that the distribution tends to uniform for p -> Inf, but pnormp and rnormp break down for quite modest values of p. As p -> 0 it tends to a point distribution at 0, but you will see very large values far too often. So if you want p smaller than say 0.01 you will need to implement a different algorithm.
Regards,
Iwona Szydlowska
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______________________________________________ R-help at stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
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 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595
Il giorno mar, 24/07/2007 alle 06.39 +0100, Prof Brian Ripley ha scritto:
On Mon, 23 Jul 2007, Iwona Szyd?owska wrote:
Hello,
I would like to ask You, how to generate random numbers from an exponential power family with a shape parameter p less than 1(p->0). I found the rnormp package, which can generate numbers from this distribution, but only for parameter less or equal 1.
It seems you mean package 'normalp', and that the package author believes that the exponential power distribution is only defined for p >= 1 (although that is not on the help page). Other authors believe it is defined by a relationship to the gamma for all p > 0. So all you need to do is to change the condition from p < 1 to p <= 0 in rnormp and friends.
Well, I know that an exponential power distribution is defined for p>0, (I think quite all the references I know consider p>0), but for 0<p<1 the algorithms that I have implemented for the estimates of the distribution parameters and for the regression parameters are really instable (pratically are not usable at all). Then, I prefered for all the functions of the normalp package consider only the case p>=1. All the best, Angelo Mineo
However, the algorithms used are not adequate for large or small p. We know that the distribution tends to uniform for p -> Inf, but pnormp and rnormp break down for quite modest values of p. As p -> 0 it tends to a point distribution at 0, but you will see very large values far too often. So if you want p smaller than say 0.01 you will need to implement a different algorithm.
Regards,
Iwona Szydlowska
[[alternative HTML version deleted]]
______________________________________________ R-help at stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.