In this work we discuss a novel framework for modelling complex inter- actions in spatio-temporal datasets. The joint effect due to the space and time (in- teraction term) is separated out by the marginal effects. To implement these models in a Bayesian framework we find convenient to work under the Penalized Complexity (PC) prior framework. In this way, the degree with which the interaction model shrinks to the marginal model can intuitively be tuned at prior.

Ventrucci M, F.M. (2019). Modelling complex interactions in spatio-temporal datasets.

Modelling complex interactions in spatio-temporal datasets

Ventrucci M
;
2019

Abstract

In this work we discuss a novel framework for modelling complex inter- actions in spatio-temporal datasets. The joint effect due to the space and time (in- teraction term) is separated out by the marginal effects. To implement these models in a Bayesian framework we find convenient to work under the Penalized Complexity (PC) prior framework. In this way, the degree with which the interaction model shrinks to the marginal model can intuitively be tuned at prior.
2019
SIS 2019 - Smart Statistics for smart applications
1
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Ventrucci M, F.M. (2019). Modelling complex interactions in spatio-temporal datasets.
Ventrucci M, Franco-Villoria M, Rue H
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/709727
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