A0659
Title: Local maxima of discrete Gaussian processes
Authors: Dan Cheng - Arizona State University (United States) [presenting]
Abstract: The expected number and height distribution of local maxima are derived for Gaussian processes defined on discrete parameter sets. It is further demonstrated that as the discrete sets become increasingly dense, the expected number and height distribution will converge to those of the corresponding continuous Gaussian processes, respectively. Since real-world datasets are typically discrete, findings offer valuable insights for statistical applications, including signal detection and change point detection.
