Zhaoying Lu PhD Final Defense 07/27/23 3pm on Zoom

Title: Simultaneous Change-point Detection and Curve Estimation for Single and Multiple Sequential Data

Abstract: In this dissertation, we propose new nonparametric regression methods that account for discontinuities in single and multiple sequential data. The new method is called Simultaneous CHange-point detection And Curve Estimation (SCHACE), which can automatically detect jumps in data sequences and, at the same time, accurately capture nonlinear trends between these jumps in the mean curve. This approach is a single-step method that does not require iteration and is, therefore, computationally efficient and fast to implement. To evaluate the performance of SCHACE, I conduct extensive numerical experiments, including both simulated and real-world data examples. I also study the problem of change-point detection for multiple data sequences simultaneously. Furthermore, I propose two variants to generalize SCHACE by integrating group Lasso for change-point detection in multiple sequences and B-splines for nonparametric regression curve estimation. 

Time: Thursday, July 27th, at 3 PM (Tucson time)

Zoom Link: https://arizona.zoom.us/j/83898366055