ONLINE COURSE – Introduction to Bayesian modelling with INLA (BMIN02) This course will be delivered live
21 June 2021 - 25 June 2021
£520
This course will now be delivered live by video link in light of travel restrictions due to the COVID-19 (Coronavirus) outbreak.
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 – Central European Standard Time (CEST) – however all sessions will be recorded and made available allowing attendees from different time zones to follow a day behind (please email oliverhooker@prstatistics.com for full details or to discuss how we can accommodate you).
Please feel free to email oliverhooker@prstatistics.com with any questions, full course detials below.
Course Overview:
The aim of the course is to introduce you to Bayesian inference using the integrated nested Laplace approximation (INLA) method and its associated R-INLA package. This course will cover the basics on the INLA methodology as well as practical modelling of different types of data.
By the end of the course participants should:
- Understand the basics of Bayesian inference.
- Understand how the INLA method works and its main differences with MCMC methods.
- Be able to fit models with the R-INLA package.
- Know how to interpret the output from model fitting.
- Be confident with the use of INLA for data analysis.
- Understand the different models that can be fit with INLA.
- Know how to define the different parts of a model with INLA.
- Be able to develop new latent effects not implemented in the R-INLA package.
- Know how to define new priors not included in the R-INLA package.
- Have the confidence to use INLA for their own projects.
Intended Audience
Academics and post-graduate students working on projects related to data analysis and modelling and who want to add the INLA methodology for Bayesian inference to their toolbox.
Applied researchers and analysts in public, private or third-sector organizations who need the reproducibility, speed and flexibility of a command-line language such as R.
The course is designed for intermediate-to-advanced R users interested in data analysis and modelling. Ideally, they should have some background on probability, statistics and data analysis.
Venue – Delivered remotely
Time zone – Central European Standard Time (CEST)
Availability – 20 places
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
PLEASE READ – CANCELLATION POLICY: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact oliverhooker@prstatistics.com. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees will be credited.
Dr. Virgilio Gómez Rubio
