[R-sig-eco] probability distribution for zero-inflated, right skewed data

[Scott Foster]

Hi,

Just a little note about computational methods for Tweedies and compound Poisson-gammas.  The package statMod has a Tweedie family that can be used in 
glm(), the package Tweedie has functions for density calculations (and other things), the package fishMod (my own package) has methods to fit Tweedie 
GLMs and compound Poisson-gamma, and lastly (but very far from leastly) mgcv has a Tweedie family too.  The mgcv fact seems to not be widely known.

None of these methods are Bayesian however.  As Bob suggested coding up a sampler should be easy enough, either from the compound representation or 
directly from the (marginal) Tweedie -- see ?rTweedie in the fishMod package or ?rtweedie in the tweedie package.

At the risk of blatant self-promotion have a look at my paper on compound Poisson-gammas -- there is a review of some of the more common methods. 
http://link.springer.com/article/10.1007/s10651-012-0233-0

Good luck!

Scott

On 16/06/14 22:29, Bob O'Hara wrote:
> On 16/06/14 13:57, Johannes Björk wrote:
>> Dear all,
>>
>> Im looking into how to fit a GLM model (Im using rjags) with data that are heavily right skewed. In addition, some variables also zero-inflated. 
>> The data are species area distribution measured as "total area (km^2)" which is subsetted into "area in tropical zone" and "area in temperate 
>> zone". The last two variables contain zeros.
>>
>> I have google zero-inflated models... and most that come up is "zero-inflated negative binomial" and zero-inflated negative poisson" for count 
>> data. I reckon I cannot use any of these distributions since my variables are not discrete.
>>
>> Any pointer to which distribution(s) that might fit this kind of data would be much appreciated.
> I think a Tweedie distribution is sometimes used, but that always makes me think of escaping chickens. Recently this was published, which might also 
> be useful: <http://onlinelibrary.wiley.com/doi/10.1111/2041-210X.12122/abstract>. They used BUGS, so you could ask them if the code is available. 
> Even if it isn't, it shouldn't be too difficult to code up.
>
> Bob
>

-- 
Scott Foster
Computational Informatics
CSIRO
E scott.foster at csiro.au T +61 3 6232 5178
Postal address: CSIRO Computational Informatics, GPO Box 1538, Hobart TAS 7001
Street Address: CSIRO Computational Informatics, Castray Esplanade, Hobart Tas 7001, Australia
www.csiro.au