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03/24/2023
On the failure of the bootstrap for Chatterjee's rank correlation
While researchers commonly use the bootstrap for statistical inference, ...
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12/11/2022
On regression-adjusted imputation estimators of the average treatment effect
Imputing missing potential outcomes using an estimated regression functi...
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09/22/2022
Azadkia-Chatterjee's correlation coefficient adapts to manifold data
In their seminal work, Azadkia and Chatterjee (2021) initiated graph-bas...
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04/17/2022
Limit theorems of Chatterjee's rank correlation
Establishing the limiting distribution of Chatterjee's rank correlation ...
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12/04/2021
Nonparametric mixture MLEs under Gaussian-smoothed optimal transport distance
The Gaussian-smoothed optimal transport (GOT) framework, pioneered in Go...
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11/30/2021
Center-Outward Sign- and Rank-Based Quadrant, Spearman, and Kendall Tests for Multivariate Independence
Defining multivariate generalizations of the classical univariate ranks ...
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08/15/2021
On boosting the power of Chatterjee's rank correlation
Chatterjee (2021)'s ingenious approach to estimating a measure of depend...
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08/15/2021
On Azadkia-Chatterjee's conditional dependence coefficient
In recent work, Azadkia and Chatterjee laid out an ingenious approach to...
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06/06/2021
Fisher-Pitman permutation tests based on nonparametric Poisson mixtures with application to single cell genomics
This paper investigates the theoretical and empirical performance of Fis...
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01/16/2021
Robust Functional Principal Component Analysis via Functional Pairwise Spatial Signs
Functional principal component analysis (FPCA) has been widely used to c...
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08/26/2020
On the power of Chatterjee rank correlation
Chatterjee (2020) introduced a simple new rank correlation coefficient t...
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07/04/2020
Rate-optimality of consistent distribution-free tests of independence based on center-outward ranks and signs
Rank correlations have found many innovative applications in the last de...
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04/23/2020
On a phase transition in general order spline regression
In the Gaussian sequence model Y= θ_0 + ε in R^n, we study the fundament...
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01/05/2020
Exponential inequalities for dependent V-statistics via random Fourier features
We establish exponential inequalities for a class of V-statistics under ...
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09/22/2019
Distribution-free consistent independence tests via Hallin's multivariate rank
This paper investigates the problem of testing independence of two rando...
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08/14/2019
On rank estimators in increasing dimensions
The family of rank estimators, including Han's maximum rank correlation ...
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07/15/2019
Probability inequalities for high dimensional time series under a triangular array framework
Study of time series data often involves measuring the strength of tempo...
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06/23/2019
Asymptotic joint distribution of extreme eigenvalues and trace of large sample covariance matrix in a generalized spiked population model
This paper studies the joint limiting behavior of extreme eigenvalues an...
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02/27/2019
Optimal estimation of variance in nonparametric regression with random design
Consider the heteroscedastic nonparametric regression model with random ...
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02/07/2019
Tail behavior of dependent V-statistics and its applications
We establish exponential inequalities and Cramer-type moderate deviation...
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12/14/2018
High dimensional independence testing with maxima of rank correlations
Testing mutual independence for high dimensional observations is a funda...
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09/24/2018
Moment bounds for autocovariance matrices under dependence
The goal of this paper is to obtain expectation bounds for the deviation...
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03/30/2018
On inference validity of weighted U-statistics under data heterogeneity
Motivated by challenges on studying a new correlation measurement being ...
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04/30/2017
Testing the science/technology relationship by analysis of patent citations of scientific papers after decomposition of both science and technology
The relationship of scientific knowledge development to technological de...
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02/11/2015
An Extreme-Value Approach for Testing the Equality of Large U-Statistic Based Correlation Matrices
There has been an increasing interest in testing the equality of large P...
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02/18/2014
High Dimensional Semiparametric Scale-Invariant Principal Component Analysis
We propose a new high dimensional semiparametric principal component ana...
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08/07/2013
Challenges of Big Data Analysis
Big Data bring new opportunities to modern society and challenges to dat...
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07/01/2013
A Direct Estimation of High Dimensional Stationary Vector Autoregressions
The vector autoregressive (VAR) model is a powerful tool in modeling com...
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06/30/2013
Sparse Principal Component Analysis for High Dimensional Vector Autoregressive Models
We study sparse principal component analysis for high dimensional vector...
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05/29/2013
Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution
Correlation matrices play a key role in many multivariate methods (e.g.,...
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06/27/2012
The Nonparanormal SKEPTIC
We propose a semiparametric approach, named nonparanormal skeptic, for e...
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02/10/2012