[R] Slightly off-topic --- distribution name.
David Scott
d.scott at auckland.ac.nz
Thu Sep 16 00:00:26 CEST 2004
I believe this is the skew-Laplace distribution, although the skew-Laplace
does allow for the location of the mode of the distribution to vary.
Have a look at the function dskewlap in HyperbolicDist. The help on that
function gives a reference to a paper by Feiller et al which describes the
distribution.
David Scott
On Wed, 15 Sep 2004, Rolf Turner wrote:
>
> I've built R functions to ``effect'' a particular distribution, and
> would like to find out if that distribution is already ``known'' by
> an existing name. (I.e. suppose it were called the ``Melvin''
> distribution --- I've built dmelvin, pmelvin, qmelvin, and rmelvin as
> it were, but I need a real name to substitute for melvin.)
>
> The distribution is really just a toy --- but it provides a nice (and
> ``non-obviouse'') example of a two parameter distribution where both
> the moment and maximum likelihood equations for the parameter
> estimators are readily solvable, but at the same time are
> ``interesting''. So it's good for exercises in an intro math-stats
> course.
>
> The distribution is simply that of the ***difference*** of two
> independent exponential variates, with different parameters.
>
> I.e. X = U - V where U ~ exp(beta) and V ~ exp(alpha) (where
> E(U) = beta, E(V) = alpha).
>
> This makes the distribution of X something like an asymetric Laplace
> distribution, with its mode at 0. (One could shift the mode too, but
> that would add a third parameter, which would be de trop.)
>
> Anyhow: Is this a ``known'' distribution? Does it have a name?
> (I've never seen it mentioned in any of the intro math-stat books
> that I've looked into.) If not, can anyone suggest a good name for
> it? (Don't be rude now!)
>
> cheers,
>
> Rolf Turner
> rolf at math.unb.ca
>
> P. S. To save you putting pen to paper and working it out,
> the density function is
>
> { exp(x/alpha)/(alpha + beta) for x <= 0
> f(x) = {
> { exp(-x/beta)/(alpha + beta) for x >= 0
>
> The mean and variance are mu = beta - alpha and
> sigma^2 = alpha^2 + beta^2 respectfully. :-)
>
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_________________________________________________________________
David Scott Department of Statistics, Tamaki Campus
The University of Auckland, PB 92019
Auckland NEW ZEALAND
Phone: +64 9 373 7599 ext 86830 Fax: +64 9 373 7000
Email: d.scott at auckland.ac.nz
Graduate Officer, Department of Statistics
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