Introduction Bayesian hierarchical models (IBHM02) http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical- modelling-using-r-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 [email protected] 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/
