IntroductionBayesianHierarchicalModels.8-12May.Scotland

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IntroductionBayesianHierarchicalModels.8-12May.Scotland

Oliver Hooker
Introduction Bayesian hierarchical models (IBHM02)

Instructor: Dr. Andrew Parnell

This course will run from 8th - 12th May 2017 at SCENE (the Scottish
Centre for Ecology and the Natural Environment), Loch Lomond National
Park, Glasgow.

Course overview:
This course will cover introductory hierarchical modelling for
real-world data sets from a Bayesian perspective. These methods lie at
the forefront of statistics research and are a vital tool in the
scientist’s toolbox. The course focuses on introducing concepts and
demonstrating good practice in hierarchical models. All methods are
demonstrated with data sets which participants can run themselves.
Participants will be taught how to fit hierarchical models using the
Bayesian modelling software Jags and Stan through the R software
interface. The course covers the full gamut from simple regression
models through to full generalised multivariate hierarchical structures.
A Bayesian approach is taken throughout, meaning that participants can
include all available information in their models and estimates all
unknown quantities with uncertainty. Participants are encouraged to
bring their own data sets for discussion with the course tutors.

Day 1
Basic concepts
• Class 1: Introduction to Bayesian Statistics
• Class 2: Linear and generalised linear models (GLMs)
• Practical: Using R, Jags and Stan for fitting GLMs
• Round table discussion: Understanding Bayesian models

Day 2 Hierarchical modelling
• Class 1: Simple hierarchical regression models
• Class 2: Hierarchical models for non-Gaussian data
• Practical: Fitting hierarchical models
• Round table discussion: Interpreting hierarchical model output

Day 3 Complex Models
• Class 1: Hierarchical models vs mixed effects models
• Class 2:  Multivariate and multi-layer hierarchical models
• Practical: Advanced examples of hierarchical models
• Round table discussion: Issues of continuous vs discrete time

Day 4 Shrinkage and Selection models
• Class 1: Shrinkage and variable selection
• Class 2: Hierarchical models and partial pooling
• Practical: Shrinkage modelling
• Round table discussion Bring your own data set

Day 5 Final Day
•       Summary and recap session, catch up time and bring your own
data.


The cost is £500 including lunches and course materials for students
and academic staff.
An accommodation package is available for an additional £250, this
includes breakfast, lunch, dinner, refreshments, accommodation and
course materials.

Please send inquiries to [hidden email] or visit the
website www.prstatistics.com

Please feel free to distribute this information anywhere you think
suitable.

Our other courses
1. ADVANCING IN STATISTICAL MODELLING USING R (December 2016, April
2017, December 2017
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr05/
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr06/
2. SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (November 2016, July
2017)
http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-spae04/
3. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R
(February 2017)
http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm03/
4. GENETIC DATA ANALYSIS USING R (TBC)
5. BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017)
http://www.prstatistics.com/course/bioinformatics-for-geneticists-and-biologists-bigb02/
6. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS
(November 2017)
7. INTRODUCTION TO STATISTICS AND R FOR BIOLOGISTS (April 2017)
http://www.prstatistics.com/course/introduction-to-statistics-and-r-for-biologists-irfb02/
8. INTRODUCTION TO PYTHON FOR BIOLOGISTS (TBC)
9. TIME SERIES MODELS FOR ECOLOGISTS AND CLIMATOLOGISTS (TBC)
10. ADVANCES IN MULTIVAIRAITE ANALYSIS OF SPATIAL ECOLOGICAL DATA (April
2017)
11. ADVANCES IN DNA TAXONOMY (TBC)
12. INTRODUCTION TO BIOINFORMATICS USING LINUX (TBC)
13. INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING
http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/
14. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (TBC)
15. PHYLOGENETIC DATA ANALYSIS USING R (TBC)
16. MODEL BASED MULTIVARIATE ANALYSIS OF ECOLOGICAL DATA USING R
(January 2017)
http://www.prstatistics.com/course/model-base-multivariate-analysis-of-abundance-data-using-r-mbmv01/
17. ADVANCED PYTHON FOR BIOLOGISTS (February 2017)
http://www.prstatistics.com/course/advanced-python-biologists-apyb01/
18. NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March)
http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/
19. GEOMETRIC MORPHOMETRICS USING R (June)
http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/
20. INTRODUCTION TO METHODS FOR REMOTE SENSING (July 2017)
21. ECOLOGICAL NICHE MODELLING (October 2017)
22. ANIMAL MOVEMENT ECOLOGY (TBC)

--
Oliver Hooker PhD.
PR statistics

3/1
128 Brunswick Street
Glasgow
G1 1TF

+44 (0) 7966500340

www.prstatistics.com
www.prstatistics.com/organiser/oliver-hooker/

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