Applied Bayesian Modelling, June
Responsible:
Trevor Bailey
Description

O Instituto de Saúde Pública da Universidade do Porto promove os seguintes cursos:

  1. Introdução à Estatística Espacial com o R (20 e 22 de junho 2016)
  2. Applied Bayesian Modelling (27, 28 e 29 de junho 2016)

Embora ambos os cursos funcionem de forma independente, o primeiro curso pode ser visto como uma introdução à Estatística Espacial e, assim, constituir uma primeira abordagem a alguns dos tópicos a desenvolver no segundo curso essencialmente focado em modelação bayesiana.

O curso dirige-se a investigadores nas áreas de Estatística, Epidemiologia, Saúde Pública e Medicina, Medicina Veterinária  com um interesse particular na modelação estatística.

 

Curso 1: 150 euros

Curso 2: 225 euros

Cursos 1 e 2: 325 euros.

 

Certificado de Participação: Será emitido um certificado de participação  aos participantes que frequentarem pelo menos 80% do curso.

Observations:
  1. Applied Bayesian Modelling

Staff: Professor Trevor Bailey, College of Engineering, Mathematics and Physical Sciences, University of Exeter, UK.

This course is designed to provide an introduction to Bayesian approaches to statistical modelling and associated methods (such as Markov Chain Monte Carlo (MCMC) techniques and variants of that. The focus will be very much on practical implementation of the methods using the statistical programming language R and related packages (including links between R and OpenBUGS).

The course will be taught over three days and will cover the following topics:

  • Introduction to Bayesian Modelling and MCMC

Review of the Bayesian Approach, MCMC and Hastings-Metropolis algorithm, model checking and inferential ideas.

  • Common Applications of Bayesian Modelling

Examples of implementing a range of standard models using R and links between R and OpenBUGS, including Linear and Generalised Linear Mixed models, survival models, temporal and spatio-temporal models, Generalised Additive models.

  • Extensions and more Advanced Ideas

A brief discussion of more advanced  techniques, including Reversible Jump (RJMCMC), and Approximate Bayesian Computation (ABC)

Throughout each of these topics opportunities will be provided  for participants to work through modelling examples and associated computer implementation for themselves

The course is appropriate for those involved in statistical analysis in application areas such as epidemiology, public health, medical statistics, environmental science and bioscience. It will assume background knowledge of routine statistical ideas such as regression and generalised linear models and related concepts and some familiarity with R. It will not assume a high level of theoretical mathematical statistical knowledge.

Tuition Fee:
225€ (Alunos, antigos alunos, funcionários da UP e médicos internos de Saúde Pública – 10% de redução; 5% de redução Sócios APE e SPE. Descontos não acumuláveis).
Schedule:
9.00-18.00
ECTS:
na
Start date:
2016-06-20
End date:
2016-06-30