Loading Events

« All Events

  • This event has passed.

ONLINE COURSE – Introduction to Bayesian modelling with INLA (BMIN02) NOT AVAILABLE

4th October 2021 - 8th October 2021

£520.00
ONLINE COURSE – Introduction to Bayesian modelling with INLA (BMIN02) NOT AVAILABLE

Event Date

Monday, October 4th, 2021

Course Format

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.

Course Program

TIME ZONE – UTC+2 – 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@prstatistics.com for full details or to discuss how we can accommodate you).

Course Details

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:

  1. Understand the basics of Bayesian inference.
  2. Understand how the INLA method works and its main differences with MCMC methods.
  3. Be able to fit models with the R-INLA package.
  4. Know how to interpret the output from model fitting.
  5. Be confident with the use of INLA for data analysis.
  6. Understand the different models that can be fit with INLA.
  7. Know how to define the different parts of a model with INLA.
  8. Be able to develop new latent effects not implemented in the R-INLA package.
  9. Know how to define new priors not included in the R-INLA package.
  10. Have the confidence to use INLA for their own projects.
Intended Audiences

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

Venue – Delivered remotely

Course Information

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.

Teaching Format

he course will be a mixture of theoretical and practical sessions. Each concept will be first described and explained, and next there will be a time to exercise the topics using provided data sets. Participants are also very welcome to bring their own data.

Assumed quantitative knowledge

The course is designed for intermediate-to-advanced R users interested in Bayesian inference for data analysis and R beginners who have prior experience with Bayesian inference.

Assumed computer background

Attendees should already have experience with R and be familiar with data from different formats (csv, tab, etc.), create simple plots, and manipulate data frames. Furthermore, knowledge of how to fit generalized linear (mixed) models using typical R functions (such as glm and lme4) will be useful.

Equipment and software requirements

A laptop/personal computer with any operating system (Linux, Windows, MacOS) and with recent versions of R (https://cran.r-project.org) and RStudio (https://www.rstudio.com) installed; both are freely available as open-source software. You will be sent a list of packages prior to the course. It is essential that you come with all necessary software and packages already installed.

https://cran.r-project.org/

Download RStudio

UNSURE ABOUT SUITABLILITY THEN PLEASE ASK oliverhooker@prstatistics.com

Assumed quantitative knowledge

Coming soon..

Assumed computer background

Coming soon..

Equipment and software requirements

Attendees will need to install/update R/RStudio and various additional R packages.

This can be done on Macs, Windows, and Linux.

R – https://cran.r-project.org/

RStudio – https://www.rstudio.com/products/rstudio/download/

Tickets

The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.
Tickets are no longer available

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.

If you are unsure about course suitability, please get in touch by email to find out more

info@clovertraining.co.uk

COURSE PROGRAMME

Monday 4th – Classes from 10:00 to 17:00

Introduction to the course
Key concepts related to Bayesian inference
Models with conjugate priors
Introduction to Bayesian hierarchical models
Computational methods for Bayesian inference
Introduction to the INLA methodology
Fitting generalized linear models with INLA and the R-INLA package
Understanding and manipulating the output from model fitting with R-INLA

Tuesday 5th – Classes from 10:00 to 17:00

Fitting generalized linear mixed models with R-INLA
Types of latent effects in R-INLA
Models with i.i.d. latent effects
Fitting multilevel models with R-INLA
Models with correlated latent effects
Fitting time series models with R-INLA

Wednesday 6th – Classes from 10:00 to 17:00

Priors in R-INLA
Setting priors in R-INLA
Introduction to Penalized Complexity priors (PC-priors)
Defining new priors in R-INLA
Spatially correlated random effects
Fitting spatial models with R-INLA
Visualizing the output from spatial models and mapping

Thursday 7th – Classes from 10:00 to 17:00

Advanced features in R-INLA
Computing linear combinations of the latent effects
Fitting models with several likelihoods
Models with shared terms
Adding linear constraints to the latent effects
Implementing new latent models in R-INLA
Imputation and missing covariates in R-INLA

Friday 8th – Classes from 10:00 to 17:00

Case studies and own data.

 

Course Instructor


 

Dr. Antoine Becker-Scarpitta

Works at – University of Helsink
Teaches – Multivariate analysis of ecological communities in R with the VEGAN package (VGNR03)
Antoine is a plant community ecologist working as a postdoctoral researcher at the University of Helsinki and as a postdoctoral fellow at the Institute of Botany of the Academy of the Czech Republic. Antoine holds a degree in Conservation Biology from the University of Paris-Sud-Orsay, and from the Natural History Museum of Paris, he obtained his PhD in Biology/Ecology from the University of Sherbrooke (Canada). Antoine’s research focuses on the temporal dynamics of biodiversity with a particular focus on the forest and Arctic vegetation. Antoine has taught community ecology, plant ecology and evolution, linear and multivariate statistics assisted on R.

Details

Start:
4th October 2021
End:
8th October 2021
Cost:
£520.00
Event Category:

Venue

Delivered remotely (United Kingdom)
Western European Time, United Kingdom + Google Map

Tickets

The numbers below include tickets for this event already in your cart. Clicking "Get Tickets" will allow you to edit any existing attendee information as well as change ticket quantities.
Tickets are no longer available