35 citations · 43 across the 11 of their papers we have counts for
11 papers
Basis Choices for Frequency Domain Statistical Independence Tests and Algorithms for Algebraic Relation Extraction
Juan Shi, Wenbo Wang, Wan Zhang +5
In this paper, we explore how different selections of basis functions impact the efficacy of frequency domain techniques in statistical independence tests, and study different algo…
Dempster-Shafer P-values: Thoughts on an Alternative Approach for Multinomial Inference
Kentaro Hoffman, Kai Zhang, Tyler McCormick +1
In this paper, we demonstrate that a new measure of evidence we developed called the Dempster-Shafer p-value which allow for insights and interpretations which retain most of the s…
BELIEF in Dependence: Leveraging Atomic Linearity in Data Bits for Rethinking Generalized Linear Models
Benjamin Brown, Kai Zhang, Xiao-Li Meng
Two linearly uncorrelated binary variables must be also independent because non-linear dependence cannot manifest with only two possible states. This inherent linearity is the atom…
BEAUTY Powered BEAST
Kai Zhang, Wan Zhang, Zhigen Zhao +1
We study distribution-free goodness-of-fit tests with the proposed Binary Expansion Approximation of UniformiTY (BEAUTY) approach. This method generalizes the renowned Euler's form…
The Binary Expansion Randomized Ensemble Test (BERET)
Duyeol Lee, Kai Zhang, Michael R. Kosorok
Recently, the binary expansion testing framework was introduced to test the independence of two continuous random variables by utilizing symmetry statistics that are complete suffi…
Penalized linear regression with high-dimensional pairwise screening
Siliang Gong, Kai Zhang, Yufeng Liu
In variable selection, most existing screening methods focus on marginal effects and ignore dependence between covariates. To improve the performance of selection, we incorporate p…
Efficient Test-based Variable Selection for High-dimensional Linear Models
Siliang Gong, Kai Zhang, Yufeng Liu
Variable selection plays a fundamental role in high-dimensional data analysis. Various methods have been developed for variable selection in recent years. Well-known examples are f…
BET on Independence
Kai Zhang
We study the problem of nonparametric dependence detection. Many existing methods may suffer severe power loss due to non-uniform consistency, which we illustrate with a paradox. T…
Uniform Correlation Mixture of Bivariate Normal Distributions and Hypercubically-contoured Densities That Are Marginally Normal
Kai Zhang, Lawrence D. Brown, Edward George +1
The bivariate normal density with unit variance and correlation is well-known. We show that by integrating out , the result is a function of the maximum norm. The Bayesian i…
A testing-based approach to the discovery of differentially correlated variable sets
Kelly Bodwin, Kai Zhang, Andrew Nobel
Given data obtained under two sampling conditions, it is often of interest to identify variables that behave differently in one condition than in the other. We introduce a method f…
Rank-Extreme Association of Gaussian Vectors and Low-Rank Detection
Kai Zhang
We study the spherical cap packing problem with a probabilistic approach. Such probabilistic considerations result in an asymptotic sharp universal uniform bound on the maximal inn…