Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 7 of 7 for “"Integrated Nested Laplace Approximation"”.
-
Bayesian spatio-temporal modelling, mapping and prediction of disease risk
… Bayesian εκτίμηση πραγματοποιείται με τη μέθοδο Integrated Nested Laplace Approximation (INLA), η οποία είναι κατάλληλη για λανθάνοντα Γκαουσιανά μοντέλα υψηλής διάστασης. Η προτεινόμενη μεθοδολογία εφαρμόζεται σε προσομοιωμένα επιδημιολογικά δεδομένα που αναπαριστούν τη χωρική και χρονική …
-
Computational Bayesian inference using low discrepancy sequences
The Integrated Nested Laplace Approximation (INLA) provides fast and accurate Bayesian inference for complex hierarchical models. For INLA, and other deterministic methods, the hyperparameter space is explored and points are laid out in a grid structure. These points are used in some numerical …
-
Advances in spatial modeling for complex data with applications to symbolic data and spatial transcriptomics.
… Bayesian inference facilitated through the Integrated Nested Laplace Approximation (INLA). A bivariate visualization tool is also developed to aid interpretation of the joint behavior of these features across space. Third, SPHERE (Spatial Poisson Hierarchical modEl with pathway-infoRmed gEne …
-
Models and methods for computationally efficient analysis of large spatial and spatio-temporal data
… large spatial and spatio-temporal data. Several approximation methods to "the big n problem" are reviewed, and an extended autoregressive model, called the EAR model, is proposed as a parsimonious model that accounts for smoothness of a process collected over space. It is an extension of the …
-
Modelling the spatial and temporal distribution of Bacillus anthracis suitability across Uganda and Kenya: A Bayesian Approach
… used. I discuss the application of the Integrated Nested Laplace Approximation (INLA), a spatial method that can be applied to structurally complex data, to model the suitability of B. anthracis. In Chapter 3, I apply a common conventional algorithm to analyse a 15- year dataset …
-
Adaptive robotic search and sampling of sparse natural phenomena
… probabilistic model is developed using the Integrated Nested Laplace Approximation framework, that enables online inference about expected target hotspots using predicted substrate distributions. Model parameters are learned online to build a prediction over the discrete targets, and the …
-
Adaptive Robotic Search and Sampling of Sparse Natural Phenomena
… probabilistic model is developed using the Integrated Nested Laplace Approximation framework, that enables online inference about expected target hotspots using predicted substrate distributions. Model parameters are learned online to build a prediction over the discrete targets, and the …