Comparing Bayesian statistical modelling with machine learning in spatio-temporal disease mapping
Fecha
2023Autor
Director
Versión
Acceso abierto / Sarbide irekia
Tipo
Trabajo Fin de Grado/Gradu Amaierako Lana
Impacto
|
nodoi-noplumx
|
Resumen
I have decided to embark on a new project to deepen my knowledge of
Bayesian inference and space-time modelling. I am particularly interested in exploring the use of the
Integrated Nested Laplace Approximation (INLA) methodology, which allows for fast and accurate
approximations of posterior distributions, making it an ideal tool for analyzing large and complex
datasets.
Additionally, I plan ...
[++]
I have decided to embark on a new project to deepen my knowledge of
Bayesian inference and space-time modelling. I am particularly interested in exploring the use of the
Integrated Nested Laplace Approximation (INLA) methodology, which allows for fast and accurate
approximations of posterior distributions, making it an ideal tool for analyzing large and complex
datasets.
Additionally, I plan to compare classical machine learning models such as Extreme Gradient Boosting
or Random Forest and deep learning models such as Long-Short Term Memory (LSTM) or Bayesian
Neural Network (BNN) with Bayesian statistical models fitted with INLA to determine their strengths
and weaknesses. By identifying which modelling approach is best suited for different types of datasets
and analysis tasks, I aim to become a more versatile data analyst.
To these ends, we first introduce the theoretical framework explaining the concepts of Bayesian
inference, classical machine learning and deep learning in Chapter 2. In Chapter 3, we perform an
exploratory data analysis to gain a better understanding of the problem we are facing. Subsequently,
rate modelling is presented in Chapter 4, where we outline the advantages and drawbacks of each
method. We end this work in Chapter 5 with the conclusions and ideas on further work. [--]
Materias
Bayesian inference,
Space-time modelling,
Integrated Nested Laplace Approximation (INLA),
Machine learning
Titulación
Graduado o Graduada en Ciencia de Datos por la Universidad Pública de Navarra /
Datu Zientzietan Graduatua Nafarroako Unibertsitate Publikoan