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.
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.File in questo prodotto:
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