Tiefeng Jiang | DeepAI

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Featured Co-authors

Ping Li
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Yandi Shen
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Binghui Liu
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∙ 04/25/2023

Asymptotic Distributions of Largest Pearson Correlation Coefficients under Dependent Structures

Given a random sample from a multivariate normal distribution whose cova...

0 Tiefeng Jiang, et al. ∙

∙ 05/03/2022

Asymptotic Independence of the Sum and Maximum of Dependent Random Variables with Applications to High-Dimensional Tests

For a set of dependent random variables, without stationary or the stron...

0 Long Feng, et al. ∙

∙ 08/16/2021

Mean Test with Fewer Observation than Dimension and Ratio Unbiased Estimator for Correlation Matrix

Hotelling's T-squared test is a classical tool to test if the normal mea...

0 Tiefeng Jiang, et al. ∙

∙ 01/26/2021

A general method for power analysis in testing high dimensional covariance matrices

Covariance matrix testing for high dimensional data is a fundamental pro...

0 Qiyang Han, et al. ∙

∙ 07/08/2020

Max-sum tests for cross-sectional dependence of high-demensional panel data

We consider a testing problem for cross-sectional dependence for high-di...

0 Long Feng, et al. ∙

∙ 10/28/2019

Limiting behavior of largest entry of random tensor constructed by high-dimensional data

Let X_k=(x_k1, ..., x_kp)', k=1,...,n, be a random sample of size n comi...

0 Tiefeng Jiang, et al. ∙

∙ 05/21/2019

Asymptotic Analysis for Extreme Eigenvalues of Principal Minors of Random Matrices

Consider a standard white Wishart matrix with parameters n and p. Motiva...

0 T. Tony Cai, et al. ∙

∙ 12/17/2018

Likelihood Ratio Test in Multivariate Linear Regression: from Low to High Dimension

Multivariate linear regressions are widely used statistical tools in man...

0 Yinqiu He, et al. ∙

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