I think that the (impressive) gamlss package (see
http://www.gamlss.com) may be helpful.
If I remember correctly, in gamlss you can fit model with zero-inflated
continuous distributions
hope this helps you,
vito
Alain Zuur ha scritto:
JPS2009 wrote:
Sorry bit of a Newbie question, and I promise I have searched the forum
already, but I'm getting a bit desperate!
I have over-dispersed, zero inflated data, with variance greater than the
mean, suggesting Zero-Inflated Negative Binomial - which I attempted in R
with the pscl package suggested on
http://www.ats.ucla.edu/stat/R/dae/zinbreg.htm
However my data is non-integer with some pesky decimals (i.e. 33.12) and
zinb / pscl doesn't like that - not surprising as zinb is for count data,
normally whole integers etc.
Does anyone know of a different zinb package that will allow non-integers
or and equivalent test/ model to zinb for non-integer data? Or should I
try something else like a quasi-Poisson GLM?
Apologies for the Newbie question! Any help much appreciated!
Thanks!
Is it really non-integer...or is it a density (in which case you could use
NB + offset)?
The quasi-Poisson will not help you with the zero inflation.
I'm afraid you will have to do some hard programming by combining the 0-1
binomial part with a continuous distribution on the second part of the
data......and I guess the easiest is to do this in MCMC. Perhaps the Gamma
distribution can be used? You would have to adjust all likelihood equations
as Gamma doesn't allow for zeros. But perhaps another continuous
distribution is more appropriate...depends on your data.
Alain Zuur
--
====================================
Vito M.R. Muggeo
Dip.to Sc Statist e Matem `Vianelli'
Università di Palermo
viale delle Scienze, edificio 13
90128 Palermo - ITALY
tel: 091 6626240
fax: 091 485726/485612
http://dssm.unipa.it/vmuggeo
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