132 citations · 158 across the 8 of their papers we have counts for
8 papers
Autocorrelation Test under Frequent Mean Shifts
Ziyang Liu, Ning Hao, Yue Selena Niu +2
Testing for the presence of autocorrelation is a fundamental problem in time series analysis. Classical methods such as the Box-Pierce test rely on the assumption of stationarity,…
Kernel Density Balancing
John Park, Ning Hao, Yue Selena Niu +1
High-throughput chromatin conformation capture (Hi-C) data provide insights into the 3D structure of chromosomes, with normalization being a crucial pre-processing step. A common t…
Equivariant Variance Estimation for Multiple Change-point Model
Ning Hao, Yue Selena Niu, Han Xiao
The variance of noise plays an important role in many change-point detection procedures and the associated inferences. Most commonly used variance estimators require strong assumpt…
A super scalable algorithm for short segment detection
Ning Hao, Yue Selena Niu, Feifei Xiao +1
In many applications such as copy number variant (CNV) detection, the goal is to identify short segments on which the observations have different means or medians from the backgrou…
Multiple Change-point Detection: a Selective Overview
Yue S. Niu, Ning Hao, Heping Zhang
Very long and noisy sequence data arise from biological sciences to social science including high throughput data in genomics and stock prices in econometrics. Often such data are…
A New Reduced-Rank Linear Discriminant Analysis Method and Its Applications
Yue Selena Niu, Ning Hao, Bin Dong
We consider multi-class classification problems for high dimensional data. Following the idea of reduced-rank linear discriminant analysis (LDA), we introduce a new dimension reduc…