Alan Gelfand: Spatial data and Gaussian processes - A beautiful marriage

Prof. Alan Gelfand (Duke University, Dept. of Statistical Science) will give a seminar in room 108, ground floor N.H. Abel's Building at 15:15 October 13th.

Title: Spatial data and Gaussian processes: A beautiful marriage

Abstract: In the past twenty years analysis of spatial data has become increasingly model-based. Full specification of stochastic models for the spatial process being investigated enables full inference and uncertainty assessment regarding the process. Gaussian processes on subsets of \(\mathbb R^2\) have become a fundamental specification for such modeling, particularly in settings where prediction is a primary goal. Therefore, focusing on the point-referenced case, we elaborate the substantial range of spatial settings where Gaussian processes have enabled rich and flexible modeling.

Published Sep. 3, 2015 2:37 PM - Last modified Sep. 18, 2015 6:51 PM