Alain- Thanks again for your reply. Yes, the offset for effort is only in the count part of the model. Sorry I wasn't clear about why I was using 'sum'...my effort data set contains records of trips with the effort given for each trip. I thought using sum would get me the total number of turtles predicted for the new effort data. I did also log-transform the effort in the new effort data before applying predict (correct?). I will try the manual method as you recommended to help me understand the code.
Thanks, Laura From: Alain Zuur [via R] [mailto:ml-node+s789695n4636025...@n4.nabble.com] Sent: Tuesday, July 10, 2012 1:52 PM To: Lee, Laura Subject: Re: Predicted values for zero-inflated Poisson *Laura Lee* laura.lee at ncdenr.gov <mailto:r-help%40r-project.org?Subject=Re%3A%20%5BR%5D%20Predicted%20values%20for%20zero-inflated%20Poisson&In-Reply-To=%3C1341937636301-4636016.post%40n4.nabble.com%3E> /Tue Jul 10 18:27:16 CEST 2012/ ------------------------------------------------------------------------ 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 Why do you use the sum? If you use: PredY <- predict(ZIP, type = "response") then you have predicted values for each of the rows in your effort data frame. Job done. You have an offset in your model, isn't it? You will need to choose values for this in the data frame effort as well. Also double check that the offset is only in the count part....at least that is what I would do. Note that using an offset means that you assume that if sampling effort is doubled, your fish (?) numbers double. If you fully want to understand what predict is doing, try to do it manually. Below is R code from Chapter 7 (Zero Inflation and GLMM with R) M3 <- zeroinfl(ParrotFish ~ Depth + Slope + SQDistRck + DistSed + Swell + Chla + SST, dist = "poisson", link = "logit", data = PF2) Betas.logistic <- coef(M3, model = "zero") X.logistic <- model.matrix(M3, model = "zero") eta.logistic <- X.logistic %*% Betas.logistic p <- exp(eta.logistic) / (1 + exp(eta.logistic)) Betas.log <- coef(M3, model = "count") X.log <- model.matrix(M3, model = "count") eta.log <- X.log %*% Betas.log mu <- exp(eta.log) ExpY <- mu * (1 - p) VarY <- (1 - p) * (mu + p * mu^2) Instead of using model.matrix(M3), you could specify your own data frame with covariates. Your effort. Something like: M4 <- zeroinfl(ParrotFish ~ Depth + Slope | SST, dist = "poisson", link = "logit", data = PF2) betapois <- coef(M4, model = "count") betaBin <- coef(M4, model = "zero") MyDataPois <- data.frame(Depth = blah blah, Slope = Blah blah) MyDataBin <- data.frame(SST = blah) Xpois <- model.matrix(~ blah blah, data = MyDataPois) Xbin <- model.matrix(~ blah blah, data = MyDataBin) eta.Pois <- Xpois %*% betapois eta.Bin <- blah blah mu = blah blah pi = blah blah ExpY = ... Doing it like this means you fully understand it..:-) 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 Tel: 0044 1358 788177 Email: [hidden email]</user/SendEmail.jtp?type=node&node=4636025&i=0> URL: www.highstat.com<http://www.highstat.com> URL: www.brodgar.com<http://www.brodgar.com> [[alternative HTML version deleted]] ______________________________________________ [hidden email]</user/SendEmail.jtp?type=node&node=4636025&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: highs...@highstat.com<mailto:highs...@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-tp4635861p4636025.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....@ncdenr.gov -- View this message in context: http://r.789695.n4.nabble.com/Predicted-values-for-zero-inflated-Poisson-tp4635861p4636030.html Sent from the R help mailing list archive at Nabble.com. [[alternative HTML version deleted]] ______________________________________________ R-help@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.
