DMS Statistics and Data Science Seminar

Speaker: Debashis Mondal (Oregon State University)

Title: H-likelihood Methods in Spatial Statistics

Abstract: Youngjo Lee and John Nelder introduced an important body of literature on h-likelihood methods and hierarchical generalized linear models, which expanded the scope of generalized linear regressions with correlated errors and revived an interest in Charles Roy Henderson's pioneering ideas on mixed linear equations and best linear unbiased predictions. In this talk, I shall present my work on how the h-likelihood methods pave the way for a deeper understanding of kriging and residual maximum likelihood estimation in spatial statistics, particularly for models based on conditional and intrinsic auto-regressions, de Wijs process and fractional Gaussian fields. In addition, I shall discuss how h-likelihood methods allow for scalable matrix-free computations. The importance of these developments will be emphasized with applications from environmental science. At the end, I will mention some of my ongoing works.

ZOOM: https://auburn.zoom.us/j/83299681626?pwd=SjlGNi9MWWhEMExGM0c0QzBPK0hMZz09