4 citations · 8 across the 7 of their papers we have counts for
7 papers
Change Point Localization and Inference in Dynamic Multilayer Networks
Fan Wang, Kyle Ritscher, Yik Lun Kei +2
We study offline change point localization and inference in dynamic multilayer random dot product graphs (D-MRDPGs), where at each time point, a multilayer network is observed with…
Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces
Marcos Matabuena, Rahul Ghosal, Pavlo Mozharovskyi +2
Depth measures are powerful tools for defining level sets in emerging, non--standard, and complex random objects such as high-dimensional multivariate data, functional data, and ra…
Change point detection and inference in multivariable nonparametric models under mixing conditions
Carlos Misael Madrid Padilla, Haotian Xu, Daren Wang +2
This paper studies multivariate nonparametric change point localization and inference problems. The data consists of a multivariate time series with potentially short range depende…
Kernel Biclustering algorithm in Hilbert Spaces
Marcos Matabuena, J. C Vidal, Oscar Hernan Madrid Padilla +1
Biclustering algorithms partition data and covariates simultaneously, providing new insights in several domains, such as analyzing gene expression to discover new biological functi…
Energy distance and kernel mean embeddings for two-sample survival testing
Marcos Matabuena, Oscar Hernan Madrid Padilla
We study the comparison problem of distribution equality between two random samples under a right censoring scheme. To address this problem, we design a series of tests based on en…
Sequential nonparametric tests for a change in distribution: an application to detecting radiological anomalies
Oscar Hernan Madrid Padilla, Alex Athey, Alex Reinhart +1
We propose a sequential nonparametric test for detecting a change in distribution, based on windowed Kolmogorov--Smirnov statistics. The approach is simple, robust, highly computat…