21 citations · 39 across the 5 of their papers we have counts for
6 papers · 1 filter
Change-point Detection for Sparse and Dense Functional Data in General Dimensions
Carlos Misael Madrid Padilla, Daren Wang, Zifeng Zhao +1
We study the problem of change-point detection and localisation for functional data sequentially observed on a general d-dimensional space, where we allow the functional curves to…
Functional Autoregressive Processes in Reproducing Kernel Hilbert Spaces
Daren Wang, Zifeng Zhao, Rebecca Willett +1
We study the estimation and prediction of functional autoregressive~(FAR) processes, a statistical tool for modeling functional time series data. Due to the infinite-dimensional na…
Localizing Changes in High-Dimensional Regression Models
Alessandro Rinaldo, Daren Wang, Qin Wen +2
This paper addresses the problem of localizing change points in high-dimensional linear regression models with piecewise constant regression coefficients. We develop a dynamic prog…
Detecting Abrupt Changes in High-Dimensional Self-Exciting Poisson Processes
Daren Wang, Yi Yu, Rebecca Willett
High-dimensional self-exciting point processes have been widely used in many application areas to model discrete event data in which past and current events affect the likelihood o…
Optimal nonparametric change point detection and localization
Oscar Hernan Madrid Padilla, Yi Yu, Daren Wang +1
We study change point detection and localization for univariate data in fully nonparametric settings in which, at each time point, we acquire an i.i.d. sample from an unknown distr…
Optimal Change Point Detection and Localization in Sparse Dynamic Networks
Daren Wang, Yi Yu, Alessandro Rinaldo
We study the problem of change point localization in dynamic networks models. We assume that we observe a sequence of independent adjacency matrices of the same size, each correspo…