Conveners
Session: Statistical Modeling
- François Septier (Université Bretagne Sud (UBS))
Session: Statistical Modeling
- Daisuke Murakami (The Institute of Statistical Mathematics (ISM))
Session: Statistical Modeling
- Keisuke Yano (The Institute of Statistical Mathematics (ISM))
As global warming progresses, it is increasingly important to monitor and analyse spatio-temporal patterns of heat waves and other extreme climate-related events that impact urban areas. In this work, we present a novel dynamic spatio-temporal model by combining a state space model (SSM) and a generalised hyperbolic distribution to flexibly describe a spatial-temporal profile of the tail...
This study aggregates/combines global and local sub-models to build a fast and flexible spatially varying coefficient model. An approach inspired by the generalized product-of-experts method is used to aggregate the sub-models. The aggregated model has the following properties: (i) computationally efficient; (ii) the marginal likelihood is available in closed-form; (iii) each sub-model can be...
We propose a method to construct a joint statistical model for mixed-domain data to analyze their dependence. The model is characterized by two orthogonal parameters: the dependence parameter and the marginal parameter. To estimate the dependence parameter, a conditional inference together with a sampling procedure is proposed and is shown to provide a consistent estimator. Illustrative...
