[R-sig-ME] Bayesian hierarchical modelling using R (IBHM05)

[Oliver Hooker]

Apologies for cross posting and the flurry of posts.

Bayesian hierarchical modelling using R (IBHM05)

https://www.prstatistics.com/course/bayesian-hierarchical-modelling-using-r-ibhm05/

We still have places available

This is a ‘LIVE COURSE’ – the instructor will be delivering lectures
and coaching attendees through the accompanying computer practical’s
via video link, a good internet connection is essential.

TIME ZONE – GMT – however all sessions will be recorded and made
available allowing attendees from different time zones to follow a day
behind with an additional 1/2 days support after the official course
finish date (please email oliverhooker using prstatistics.com for full
details or to discuss how we can accommodate you).

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.

Friday 27th November – Classes from 09:30 to 17:30

Module 3: Simple hierarchical regression models
Module 4: Hierarchical models for non-Gaussian data
Practical: Fitting hierarchical models

Friday 4th December – Classes from 09:30 to 17:30

Module 5: Hierarchical models vs mixed effects models
Module 6: Multivariate and multi-layer hierarchical models
Practical: Advanced examples of hierarchical models

Friday 11th December – Classes from 09:30 to 17:30

Module 7: Shrinkage and variable selection
Module 8: Hierarchical models and partial pooling
Practical: Shrinkage modelling

-- 
Oliver Hooker PhD.
PR statistics

2020 publications;
Parallelism in eco-morphology and gene expression despite variable
evolutionary and genomic backgrounds in a Holarctic fish. PLOS
GENETICS (2020). IN PRESS

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