[R-sig-ME] Response_type_and_distribution_in_gls

Highland Statistics Ltd highstat at highstat.com
Sun Mar 11 17:18:51 CET 2018

Amal..please email the mixed modelling mailing list rather than me 

On 11/03/2018 15:40, C. AMAL D. GLELE wrote:
> Hi, dear Alain.
> I'm reading your book "Statistics of Biology and Health" and I would 
> like to ask you the two following questions regarding its chapter 7:
> 1)
> which types of response variable can be used in gls model?
> is there a way to specify the response distribution in gls?
Please have a look at Pinheiro and Bates (2000). They have a whole 
chapter on this topic. Our 2009 book also has a chapter on it.

> 2)
> I remark that there is no distribution specified (via family) for the 
> responses used: which distribution does the program takes in account 
> for the response variable?
See:   ?gls

It is a linear model using generalized least squares. Hence...Gaussian.

If you want to use other distributions, then see the help file of 
glmmTMB. For example, you can model the theta of the negative binomial 
or Gamma distributions as functions of covariates.

Kind regards,

> In advance, thanks foe your answers.
> Best and regards,
> Amal
> <https://www.avast.com/sig-email?utm_medium=email&utm_source=link&utm_campaign=sig-email&utm_content=webmail> 
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Dr. Alain F. Zuur
Highland Statistics Ltd.
9 St Clair Wynd
AB41 6DZ Newburgh, UK
Email: highstat at highstat.com
URL:   www.highstat.com

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).

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