Zero Inflated Models in R

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Introduction to Zero Inflated Models with R

- Frequentist and Bayesian approaches -

29 January - 2 February 2018


zero-inflationWhat is zero inflation?
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 and therefore zero inflated models should be used.
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.

This course is taught by Dr Alain Zuur and Dr Elena Ieno, who are the leading authorities in the world on the topic of zero-inflated models in R.



  • General introduction.
  • Short revision of Poisson and negative binomial GLMs for count data and Bernoulli GLM for absence and presence data.
    • One Poisson and negative binomial GLM exercise.
    • One Bernoulli GLM exercise.
  • Theory presentation on models for zero inflated count data using frequentist tools.
    • Mixture models (ZIP).
    • Hurdle models (ZAP).
  • Two exercises on the analysis of zero inflated count data using the pscl package.


  • Finishing ZIP and ZAP exercises.
  • Models for zero inflated continuous data (e.g. biomass data) using frequentist tools.
    • One exercise.
  • Revision of linear mixed effects models and GLMM.
    • Fitting linear mixed effects models in lme4 and glmmTMB.

Wednesday morning:

  • Zero inflated GLMMs for the analysis of count data using frequentist tools.
  • Two exercises (ZIP and ZAP GLMMs).

Wednesday afternoon:

  • Introduction to Bayesian statistics and MCMC using JAGS.
    • JAGS is similar to WinBUGS and OpenBUGS.
    • 10-step protocol for MCMC.
  • One exercise: Fitting a Poisson GLM and negative binomial GLM in JAGS.
  • A video solution for a second exercise is provided.

Thursday morning:

  • Fitting zero inflated GLMs using Bayesian tools.
  • The zero trick to fit any distribution in JAGS.
  • One exercise (fitting ZIP and ZAP GLMs in JAGS).

Thursday afternoon and Friday

  • Zero inflated GLMMs for count data using Bayesian tools
  • Two exercises.
  • Time allowing (R solution code are provided):
    • Zero inflated models for proportional data (zero inflated beta models, zero inflated binomial models).
    • Bayesian model selection using the Gibbs variable selection approach.

R code for all exercises is provided before the start of the course.

General information
Target Group The course is aimed at PhD candidates, postdocs, and other academics
Group Size Min. 20 / Max. 30 participants
Course duration 5 days
Language of instruction English
Frequency of recurrence Once every 2 or 3 years
Number of credits 1.5 ECTS
Lecturers Dr Alain Zuur & Dr Elena Ieno (Highland Statistics Ltd.)
Prior knowledge Working knowledge of R, data exploration, multiple linear regression, generalised linear modelling (Poisson, negative binomial, Bernoulli) and mixed modelling is strongly recommended, but a short revision of GLM and mixed modelling is provided. This is a non-technical course. An online quiz with approximately 30 questions will soon become available at
Recommended Literature A Beginner’s Guide to Zero Inflated Models with R. (2016) (available from
Location Wageningen University Campus
Options for accommodation Accommodation is not included in the fee of the course, but there are several possibilities in Wageningen. For information on B&Bs and hotels in Wageningen please visit Another option is Short Stay Wageningen. Furthermore Airbnb offers several rooms in the area. Note that besides the restaurants in Wageningen, there are also options to have dinner on Wageningen Campus.


Fees 1
PE&RC / SENSE / WASS PhD candidates with an approved TSP €    435,- €    485,-
a) All other PhD candidates
b) Postdocs and staff of the above mentioned Graduate Schools
€    910,- €    960,-
All others € 1.345,- € 1.395,-

1 The course fee includes all course materials, coffee/tea, and lunches. It does not include accommodation and dinners (NB: options for accommodation are given above)
2 The Early-Bird Fee applies to anyone who REGISTERS ON OR BEFORE 1 JANUARY 2018


  • If you need an invoice to complete your payment, please send an email to, including ALL relevant details that should be mentioned on the invoice (e.g., purchase order no., specific addresses, attendees, etc.).
  • The Early-Bird policy is such that the moment of REGISTRATION (and not payment) is leading for determining the fee that applies to you.
  • Please make sure that your payment is arranged within two weeks after your registration.
  • It is the participant's responsibility to make sure that he/she (or his/her secretary) completes the payment correctly and in time.
PE&RC Cancellation Conditions
  • Up to 4 (four) weeks prior to the start of the course, cancellation is free of charge.
  • Up to 2 (two) weeks prior to the start of the course, a fee of € 435,- will be charged.
  • In case of cancellation within two weeks prior to the start of the course, a fee of € 910,- will be charged.
  • If you do not show at all, a fee of € 1.345,- will nevertheless be charged.

Note: If you would like to cancel your registration, ALWAYS inform us and do not assume that by NOT paying the participation fee, your registration is automatically cancelled, because it isn't (and do note that you will be kept to the cancellation conditions).

More information

Dr Lennart Suselbeek (PE&RC)
Phone: +31 317 485426


To register, please enter your details below and click "Register".