multivariate spatial processes

SPDE-Based Geostatistical and Point Process Models for Environmental and Urban Network Applications

Damilya Saduakhas, Ph.D. Student, Statistics

Apr 15, 13:00 - 15:00

B5 R5209; Zoom Meeting 96585312249

SPDEs geostatistics oceanography monitoring multivariate spatial processes environmental applications

This thesis develops statistical models based on stochastic partial differential equations (SPDEs) for geostatistical and point process data, with applications to oceanographic monitoring, traffic safety, and urban air quality.

Mixed graphical-basis models for large nonstationary and multivariate spatial data problems

Dr. William Kleiber, Associate Professor of Applied Mathematics, University of Colorado, USA

Nov 5, 14:00 - 15:00

B1 L4 R4102

multivariate spatial processes statistical climatology and statistics for energy sciences

In this talk, we explore a graphical model representation for the stochastic coefficients relying on the specification of the sparse precision matrix. Sparsity is encouraged in an L1-penalized likelihood framework. Estimation exploits a majorization-minimization approach. The result is a flexible nonstationary spatial model that is adaptable to very large datasets.

Damilya Saduakhas

Ph.D. Student, Statistics

geospatial statistics environmental applications multivariate spatial processes