A stochastic locally diffusive model with neural network‐based deformations for global sea surface temperature. Issue 1 (9th March 2022)

• Record Type: Journal Article
• Authors: Hu, Wenjing; Fuglstad, Geir‐Arne; Castruccio, Stefano
• Is Part Of: Stat. Volume 11:Issue 1(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-03-09
• Subjects: locally diffusive model -- neural networks -- sea surface temperature -- stochastic partial differential equations; Statistics -- Periodicals; 519.2
• DOI: 10.1002/sta4.431
• Languages: English
• ISSNs: 2049-1573

Abstract

Abstract : In this work, we propose a new approach to model large, irregularly distributed spatio‐temporal global data via a locally diffusive stochastic partial differential equation (SPDE). The proposed model assumes a local deformation of the SPDE with non‐linear dependence on the covariates through a neural network. The proposed model can be fit in a computationally efficient manner using a triangulation over the sphere and sparsity of the precision matrix, as shown in an application with a large data set of simulated multi‐decadal monthly sea surface temperature.