Finn Lindgren - inlabru: Extending and simplifying the INLA interface for spatial and non-linear models
| Dates: | 23 February 2022 |
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| Times: | 14:00 - 15:00 |
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| What is it: | Seminar |
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| Organiser: | Department of Mathematics |
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| Who is it for: | University staff, External researchers, Current University students |
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| Speaker: | Finn Lindgren |
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Finn Lindgren, Professor of Statistics in the School of Mathematics at the University of Edinburgh is our speaker for the Statistics seminar series.
Title: inlabru: Extending and simplifying the INLA interface for spatial and non-linear models
Abstract: The Integrated Nested Laplace Approximation (INLA) method was developed
to handle latent Gaussian additive regression models. Combined with the
stochastic partial differential equation method for constructing
computationally efficient representations of Gaussian random fields, this
has enabled fast Bayesian analysis of a wide range of models, in particular
in environmental sciences requiring spatial and spatio-temporal random
field models.
The inlabru package extends this to a more general model
class that allows more non-linearity, and a more user-friendly interface
for specifying complex models, such as point process models and joint
models for multiple response variables and spatial covariates. By using an
iterated INLA approach, the computational power of the R-INLA implementation
is extended to a wider range of models, allowing both easier access to
complex spatial model specification, and new applications in ecology,
epidemiology, and geosciences.
In this seminar I will discuss the theoretical and practical considerations
of the inlabru method and package interface, in particular for spatial models.
Speaker
Finn Lindgren
Organisation: University of Edinburgh
Travel and Contact Information
Find event
Zoom link: https://zoom.us/j/92947173491
