[R] glm, poisson and negative binomial distribution and confidence interval

From: Stéphanie D'agata <dagatastephanie_at_gmail.com>
Date: Mon, 21 Jun 2010 14:46:01 +0200


Dear list,

I am using glm's to predict count data for a fish species inside and outside a marine reserve for three different methods of monitoring. I run glms and figured out the best model using step function for each methods used.
I predicted two values for my fish counts inside and outside the reserve using means of each of the covariates (using predict() ) therefore I have only one value for each protection effect (inside/outside), considered as my mean count.

I used either poisson distribution or negative binomial for the models as for each techniques, the distribution of the counts for a same species can be quiet different.

I now need to get a confidence interval for my predicted count and I want to compute the coefficient of variation.

It looks like the function pois.ci() (package NCstats) gives a confidence interval for a single given value

or bspln() and bsnb() ("degreenet") gives also CI but using bootstrap. I therefore need a vector of counts using those latest function, which I don't have since I have only one predicted values from my Glms.

My questions are the following:

About the coefficient of variation, is it equal to the standard deviation/ mean for all the distributions???

Can I say that for a poisson distribution, it is therefore equal to 1/sqrt(mean) and for a negative binomial distribution, variance = mean + mean^2/theta (theta the canonical parameter given in glm.nb summary). I can then calculate my St. Dev and then CV?

I really appreciate your help.

Regards,

-- 
Stéphanie D'agata

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Received on Mon 21 Jun 2010 - 12:51:29 GMT

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