ggplot of Hurdle model
---------------------------------------------------------------------- Message: 1 Date: Thu, 2 Nov 2017 14:52:29 +0100 From: andreu blanco <andreu.blanco at gmail.com> To: r-sig-mixed-models at r-project.org Subject: [R-sig-ME] ggplot of Hurdle model Message-ID: <CAOy7hbCs_niPqWPN-u+zDrgSczfi9J1pHFbPhTc6L_WunY35DQ at mail.gmail.com> Content-Type: text/plain; charset="UTF-8" According to the information in the Zuur's book "Begginers guide to Zero-inflated models with R", I see they suggest a graph to add to the research paper. However I don't know how to sketch the model fit to my results.
That book contains fully worked out ggplot2 code to sketch the two individual components of a hurdle model, and also the expected values of the actual hurdle model. Based on your str output below I see you have only factors and biomass. So..you can visualise the Bernoulli GLM, and you can also visualise the Gamma GLM. Just use geom_errorbar instead of geom_ribbon when plotting the results (because you only have factors). Being a PhD student means that you should be able to figure this out. Note that 80 observations is rather small for the things that you are (probably) doing. I hope there are no random effects involved.....though given the fact that you use glmer it seems that you do. Kind regards, Alain
My data structure is:
str(Aarmata)
'data.frame': 80 obs. of? 6 variables: ? $ Location? : Factor w/ 8 levels "C1","C2","O",..: 1 1 1 1 1 5 5 5 5 5 ... ? $ Protection: Factor w/ 2 levels "C","P": 1 1 1 1 1 2 2 2 2 2 ... ? $ Exposure? : Factor w/ 2 levels "E","S": 1 1 1 1 1 1 1 1 1 1 ... ? $ replicates: int? 1 2 3 4 5 1 2 3 4 5 ... ? $ Biomass?? : num? 124.8 104.8 139.2 102.6 62.9 ... Any suggestion would be highly appreciated. Andreu
Dr. Alain F. Zuur Highland Statistics Ltd. 9 St Clair Wynd AB41 6DZ Newburgh, UK Email: highstat at highstat.com URL: www.highstat.com And: NIOZ Royal Netherlands Institute for Sea Research, Department of Coastal Systems, and Utrecht University, P.O. Box 59, 1790 AB Den Burg, Texel, The Netherlands Author of: 1. Beginner's Guide to Spatial, Temporal and Spatial-Temporal Ecological Data Analysis with R-INLA. (2017). 2. Beginner's Guide to Zero-Inflated Models with R (2016). 3. Beginner's Guide to Data Exploration and Visualisation with R (2015). 4. Beginner's Guide to GAMM with R (2014). 5. Beginner's Guide to GLM and GLMM with R (2013). 6. Beginner's Guide to GAM with R (2012). 7. Zero Inflated Models and GLMM with R (2012). 8. A Beginner's Guide to R (2009). 9. Mixed effects models and extensions in ecology with R (2009). 10. Analysing Ecological Data (2007). [[alternative HTML version deleted]]