[R-sig-ME] New book: Spatial, Temporal and Spatial-Temporal Ecological Data Analysis with R-INLA

[Highland Statistics Ltd]

We are pleased to announce the following book:

Spatial, Temporal and Spatial-Temporal Ecological Data Analysis with R-INLA
Authors: Zuur, Ieno, Saveliev


Book website: http://highstat.com/index.php/books
Paperback or EBook can be order (exclusively) from www.highstat.com
TOC: http://highstat.com/Books/BGS/SpatialTemp/Zuuretal2017_TOCOnline.pdf


Summary: We explain how to apply linear regression models, generalised 
linear models (GLM), and generalised linear mixed-effects models (GLMM) 
to spatial, temporal, and spatial-temporal data.


Outline
In Chapter 2 we discuss an important topic: dependency. Ignoring this 
means that we have pseudoreplication. We present a series of examples 
and discuss how dependency can manifest itself.

We briefly discuss frequentist tools that are available for the analysis 
of temporal and spatial data in Chapters 3 and 4, and we will conclude 
that their application is rather limited, especially if non-Gaussian 
distributions are required. We will therefore consider alternative 
models, but these require Bayesian techniques.

In Chapter 5 we discuss linear mixed-effects models to analyse 
hierarchical (i.e. clustered or nested) data, and in Chapter 6 we 
outline how we add spatial and spatial-temporal dependency to regression 
models via spatial (and/or temporal) correlated random effects.

In Chapter 7 we introduce Bayesian analysis, Markov chain Monte Carlo 
techniques (MCMC), and Integrated Nested Laplace Approximation (INLA). 
INLA allows us to apply models to spatial, temporal, or spatial-temporal 
data.

In Chapters 8 through 16 we present a series of INLA examples. We start 
by applying linear regression and mixed-effects models in INLA (Chapters 
8 and 9), followed by GLM examples in Chapter 10. In Chapters 11 through 
13 we show how to apply GLM models on spatial data. In Chapter 14 we 
discuss time-series techniques and how to implement them in INLA. 
Finally, in Chapters 15 and 16 we analyse spatial-temporal models in INLA.





-- 
Dr. Alain F. Zuur

First author of:
1. Beginner's Guide to GAMM with R (2014).
2. Beginner's Guide to GLM and GLMM with R (2013).
3. Beginner's Guide to GAM with R (2012).
4. Zero Inflated Models and GLMM with R (2012).
5. A Beginner's Guide to R (2009).
6. Mixed effects models and extensions in ecology with R (2009).
7. Analysing Ecological Data (2007).

Highland Statistics Ltd.
9 St Clair Wynd
UK - AB41 6DZ Newburgh
Tel:   0044 1358 788177
Email: highstat at highstat.com
URL: www.highstat.com


-- 

Dr. Alain F. Zuur



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).

Highland Statistics Ltd.
9 St Clair Wynd
UK - AB41 6DZ Newburgh
Tel:   0044 1358 788177
Email: highstat at highstat.com
URL:   www.highstat.com


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