>Specifically, I have some "freezing days" data, which is a count of the
>number of days each spring that were below freezing. The counts were taken
>at the same location over a period of years. The data set is highly zero
>inflated and over-dispersed; glm with a quasipoisson error structure would
>seem to be appropriate, except that there is a high degree of correlation
>at lags of 1 making something like a corAR1 structure appropriate. My
>difficulty is that glm() does not take an argument for correlation.

>I could use  lmer() to fit a model like:

>freezing days~years+(1|years), family=quasipoisson, correlation=corAR1

>but lmer (and glmer) don't seem to be operating on quasi families anymore;>
>I've found plenty of old posts here where lmer seems to have accepted quasi
>families in the past, but I get an error message that indicates lmer does
>not in fact accept quasi families.


Lee,

Why don't you try this:


FreezingDays_s ~ Poisson(mu_s)

log(mu_s) = alpha + beta * years + eps_s
eps_s = rho * eps_s-1  + PureNoise


You can also use a smoothing function for years (though it may fight with the AR1 part).
You can fit this model in WinBUGS or OpenBUGS. Code is given in Chapter 9 of:
Zero Inflated Models and Generalized Linear Mixed Models with R. (2012). Zuur et al.
It will be out in 3-4 weeks. But a bit of googling should help you as well.


The only thing to keep in mind is that lots of sequential zeros means very (!) high auto-correlation.
Also think very careful whether your 'number of freezing days' indeed follows a Poisson distribution.
I wouldn't be surprised if it is going to be underdispersed.

I would also be careful with zero inflation and auto-correlation in the same model....they may also
compete for the same info.
  
Alain




-- 

Dr. Alain F. Zuur
First author of:

1. Analysing Ecological Data (2007).
Zuur, AF, Ieno, EN and Smith, GM. Springer. 680 p.
URL: www.springer.com/0-387-45967-7


2. Mixed effects models and extensions in ecology with R. (2009).
Zuur, AF, Ieno, EN, Walker, N, Saveliev, AA, and Smith, GM. Springer.
http://www.springer.com/life+sci/ecology/book/978-0-387-87457-9


3. A Beginner's Guide to R (2009).
Zuur, AF, Ieno, EN, Meesters, EHWG. Springer
http://www.springer.com/statistics/computational/book/978-0-387-93836-3


Other books: http://www.highstat.com/books.htm


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Highland Statistics Ltd.
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