[R] Course: Introduction to Zero Inflated Models

Highland Statistics Ltd highstat at highstat.com
Tue May 24 10:18:11 CEST 2016


There are places available on the following course:


Course: Introduction to Zero Inflated Models (Bayesian and frequentist 
approaches)

When: 13-17 June 2016

Where: Australian Institute of Marine Science, Perth, Australia

Course website: http://highstat.com/statscourse.htm

Course flyer: http://highstat.com/Courses/Flyers/Flyer2016_06Perth_ZI_V2.pdf

Keywords: Zero inflated count data. Zero inflated continuous data. 
Dependency. ZIP and ZAP models. Zero inflated GLMMs with random effects. 
Bayesian statistics, MCMC and JAGS. lme4, glmmADMB, JAGS. Overdispersion 
and solutions. Bayesian model selection.

Description: Suppose you want to study hippos and the effect of habitat 
variables on their distribution. When sampling, you may count zero 
hippos at many sites, potentially resulting in overdispersed Poisson 
GLMs.  In such cases zero inflated models can be applied. During the 
course several case studies are presented, in which the statistical 
theory for zero inflated models is integrated with applied analyses in a 
clear and understandable manner. Zero inflated models consist of two 
integrated GLMs and therefore we will start with a revision of GLM. Zero 
inflated GLMMs for nested data (repeated measurements, short time 
series, clustered data, etc.) are discussed in the second part of the 
course. We will focus on zero inflated count data, and zero inflated 
continuous data.




-- 
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


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