Bayesian and computational Statistics

Proper Random Walk Spline Models

Eman Kabbas, Ph.D. Student, Applied Mathematics and Computational Science

Nov 2, 15:00 - 17:00

B3 L5 R5209

Bayesian and computational Statistics data science

This dissertation introduces the Proper Random Walk of order 2 (PRW2), a full-rank Gaussian Markov random field that provides a principled alternative to intrinsic random walk (RW2) priors. By construction, RW2 models exhibit heteroscedastic marginal variances, inflated boundary effects, sensitivity to grid design, and unbounded forecast uncertainty—features that undermine the reliability of inference, particularly in sparse-data settings or beyond the observed domain.

Eman Kabbas

Ph.D. Student, Applied Mathematics and Computational Science

Bayesian and computational Statistics Bayesian Data Aalysis data science Applied and theoretical statistics Data Sciences

Deeply passionate about Bayesian statistics, Eman Kabbas is a Math/Statistics Lecturer in the General Studies Department at Jubail Industrial College (JIC). Currently, Eman is a Ph.D. candidate in Applied Mathematics and Computational Sciences at KAUST, specializing in Bayesian statistics under the supervision of Professor Håvard Rue.