Dear R users,
I am trying to use "gamm" from package "mgcv" to model results from a mesocosm
experiment. My model is of type
M1 <- gamm(Resp ~ s(Day, k=8) + s(Day, by=C, k=8) + Flow + offset(LogVol),
data=MyResp,
correlation = corAR1(form= ~ Day|Mesocosm),
family=poisson(link=log))
where the response variable is counts, offset by the log of sample volume.
Unfortunately, the residuals from the model show heteroscedasticity. While
trying to follow up on this, I have run into following problems:
1) How to estimate the overdispersion parameter from a (Poisson) gamm?
I have not been able to extract residual degrees of freedom from M1.
2) How to manually estimate theta for a negative binomial gamm?
I would like to see if applying a negative binomial distribution with log link
(model below) would solve the problem. However, negbin in gamm requires a known
theta...
M2 <- gamm(Resp ~ s(Day, k=8) + s(Day, by=C, k=8) + Flow + offset(LogVol),
data=MyResp,
correlation = corAR1(form= ~ Day|Mesocosm),
family= negbin(THETA, link="log"))
3) And finally, can I somehow compare the models M1 and M2? Trying anova(M1,M2)
gives the message: "Error in eval(expr, envir, enclos) : object 'fixed' not
found" (and I am anyway not sure if this is a valid approach between Poisson
and negbin gamms).
I am most grateful for any help!
Aino
Aino Hosia
Postdoc
Havforskningsinstituttet/Institute of Marine Research
PO Box 1870 Nordnes, N-5817 Bergen, Norway
(Nordnesgaten 50)
Tel: +47 55 23 53 49
E-mail: aino.ho...@imr.no<mailto:aino.ho...@imr.no>
www.imr.no<http://www.imr.no/>
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