From: Francisco Cribari <cribari@de.ufpe.br>
To: Chong Gu <chong@stat.purdue.edu>, r-help@stat.math.ethz.ch
Subject: Re: [R] inverse.gaussian, nbinom
Date: Tue, 8 Jun 1999 07:49:31 -0300
Message-Id: <99060808090204.06689@edgeworth.de.ufpe.br>
On Tue, 08 Jun 1999, Chong Gu wrote:
> 1. inverse.gaussian is up there as one of the glm families, but do
> people ever use it? There is no inverse.gaussian in the R
> distribution family, and when I checked McCullagh & Nelder, it only
> appeared twice in the book (according to subject index), once in the
> table on p. 30 and once on p. 38 in a passing sentence. Is there a
> good reference on this distribution?
See
Chhikara, R.S. & Folks, J.L. (1989). The Inverse Gaussian Distribution:
Theory, Methodology and Applications. New York: Marcel Dekker.
See also
Desmond, A.F. & Chapman, G.R. (1993). Modelling task completion data
with inverse Gaussian mixtures. Applied Statistics, 42, 603-613.
Whitmore, G.A. (1986). Inverse Gaussian ratio estimation. Applied
Statistics, 35, 8-15.
For an example where the fit of an inverse Gaussian model is better
than that of a normal or gamma model, see pp.98-101 in
Lindsey, J.K. (1997). Applying Generalized Linear Models. New York:
Springer-Verlag.
Finally, for a good and detailed discussion of the IG distribution,
see chapter 15 (pp.259-297) in
Johnson, N.L., Kotz, S. & Balakrishnan, N. (1994). Continuous Univariate
Distributions, Vol.1, 2nd ed. New York: Wiley.
Best, FC.
-- Francisco Cribari-Neto voice: +55-81-2718420 Departamento de Estatistica fax: +55-81-2718422 Universidade Federal de Pernambuco e-mail: cribari@de.ufpe.br Recife/PE, 50740-540, Brazil web: www.de.ufpe.br/~cribari/I would like to get an education, but it may be too late: I already have my doctorate.
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