[R-sig-ME] Mixed-Model-Accounting-Spatial_Correlation

[Highland Statistics Ltd]

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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>
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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

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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).