------------------------------ Message: 3 Date: Fri, 9 Mar 2018 23:51:39 +0100 From: "C. AMAL D. GLELE" <altessedac2 at gmail.com> To: R SIG Mixed Models <R-sig-mixed-models at r-project.org> Subject: [R-sig-ME] Mixed-Model-Accounting-Spatial_Correlation Message-ID: <CANrzCv037Mi2hR6ziY8WmOiZbE1aYEHgVF_1sLVhkWnKg-R61Q at mail.gmail.com> Content-Type: text/plain; charset="utf-8" Hi, dear all. Can someone please, tell me if there is ways to fit models (with, or not) random effects, accounting spatial correlation and accepting numerical and/or categorical explanatories variables? In advance, thanks for your helps. Best and regards, Amal ?------------------------------ Amal, The answer is 'yes'. See https://stat.ethz.ch/pipermail/r-sig-mixed-models/2018q1/date.html You will see about 10 posts on this topic. And see also: https://cran.r-project.org/web/packages/glmmTMB/vignettes/covstruct.html Kind regards, Alain
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).