Predicted values for zero-inflated Poisson
On Tue, 10 Jul 2012, Laura Lee wrote:
Alain- Thanks again for the response. I guess my question is more related to R, which I'm learning as I go along. Could you provide guidance as to how I would code this in R?
That depends on what exactly you want to predict. As Alain said: The type="count" predictions are probably not interesting to you. In the JSS paper accompanying zeroinfl, these correspond to exp(x'b) in Equation 8. More interesting is probably the mean (1 - pi) * exp(x'b) which is the expected mean mu_i in Equation 8. This can be obtained as type="response". Additionally, you might be interested in the individual probabilities for counts of 0, 1, 2, ... etc. This corresponds to evaluating Equation 7 for y = 0, 1, 2, ... which can be obtained via type="prob". And from this you could also get the mode or median rather than the mean of the distribution. hth, Z
Thanks,
Laura
From: Alain Zuur [via R] [mailto:ml-node+s789695n4635920h92 at n4.nabble.com]
Sent: Monday, July 09, 2012 5:20 PM
To: Lee, Laura
Subject: Re: Predicted values for zero-inflated Poisson
Laura Lee laura.lee at ncdenr.gov
Mon Jul 9 22:51:40 CEST 2012
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Thanks for your reply. I do have a copy of "Zero Inflated Models and
Generalized Linear Mixed Models with R" and have been using that as a guide.
I applied the predict function (type="count") to the dataset for which I
built the model to compare the predicted bycatch numbers to the observed to
ensure I was doing things correctly. When I summed over the new predicted
variable, the value is over 500 whereas there were less than 10 observed.
I'd appreciate any advice regarding what I'm doing wrong.
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AFZ:
Laura....no...you don't want to compare the count part of the model with raw data....you need to compare
the Exp(Y) = (1-pi) * mu with the raw data. Have a look at the Epilogue chapter....it shows the difference
between mu and (1-pi) * mu.
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<http://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
4. Zero Inflated Models and Generalized Linear Mixed Models with R. (2012) Zuur, Saveliev, Ieno.
http://www.highstat.com/book4.htm
Other books: http://www.highstat.com/books.htm
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