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Predicted values for zero-inflated Poisson
4 messages · Highland Statistics Ltd, Lee, Laura, Achim Zeileis
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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
Statistical consultancy, courses, data analysis and software
Highland Statistics Ltd.
6 Laverock road
UK - AB41 6FN Newburgh
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______________________________________________ [hidden email]</user/SendEmail.jtp?type=node&node=4635920&i=1> mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. 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 Other books: http://www.highstat.com/books.htm Statistical consultancy, courses, data analysis and software Highland Statistics Ltd. 6 Laverock road UK - AB41 6FN Newburgh Tel: 0044 1358 788177 Email: highstat at highstat.com<mailto:highstat at highstat.com> URL: www.highstat.com<http://www.highstat.com> URL: www.brodgar.com<http://www.brodgar.com> ________________________________ If you reply to this email, your message will be added to the discussion below: http://r.789695.n4.nabble.com/Predicted-values-for-zero-inflated-Poisson-tp4635861p4635920.html To unsubscribe from Predicted values for zero-inflated Poisson, click here<http://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=unsubscribe_by_code&node=4635861&code=bGF1cmEubGVlQG5jZGVuci5nb3Z8NDYzNTg2MXw0NTg5ODY5NTk=>. NAML<http://r.789695.n4.nabble.com/template/NamlServlet.jtp?macro=macro_viewer&id=instant_html%21nabble%3Aemail.naml&base=nabble.naml.namespaces.BasicNamespace-nabble.view.web.template.NabbleNamespace-nabble.view.web.template.NodeNamespace&breadcrumbs=notify_subscribers%21nabble%3Aemail.naml-instant_emails%21nabble%3Aemail.naml-send_instant_email%21nabble%3Aemail.naml> ----- Laura M. Lee Senior Stock Assessment Scientist North Carolina Division of Marine Fisheries E-Mail: laura.lee at ncdenr.gov -- View this message in context: http://r.789695.n4.nabble.com/Predicted-values-for-zero-inflated-Poisson-tp4635861p4635978.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]] ______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
I want to predict the number of turtles for different levels of effort and combinations of covariates. So, for my dataset from which I built the model, would I compare sum(predict(ZIP,type="response")) to the observed bycatch to compare numbers? In order to predict for the new data (called effort), would I use sum(predict(ZIP,newdata=effort,type="response"))? I want to be certain I am understanding the coding--this is my first time using the predict function. Thanks, Laura ----- Laura M. Lee Senior Stock Assessment Scientist North Carolina Division of Marine Fisheries E-Mail: laura.lee at ncdenr.gov -- View this message in context: http://r.789695.n4.nabble.com/Predicted-values-for-zero-inflated-Poisson-tp4635861p4636016.html Sent from the R help mailing list archive at Nabble.com.