Xin Dang

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The University of Mississippi

A rank-based Cramér-von-Mises-type test for two samples

We study a rank based univariate two-sample distribution-free test. The ...
02/18/2018 ∙ by Jamye Curry, et al. ∙ 0 ∙ share

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Robust and Efficient Boosting Method using the Conditional Risk

Well-known for its simplicity and effectiveness in classification, AdaBo...
06/21/2018 ∙ by Zhi Xiao, et al. ∙ 0 ∙ share

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Jackknife Empirical Likelihood Methods for Gini Correlations and their Equality Testing

The Gini correlation plays an important role in measuring dependence of ...
06/03/2018 ∙ by Yongli Sang, et al. ∙ 0 ∙ share

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A new Gini correlation between quantitative and qualitative variables

We propose a new Gini correlation to measure dependence between a catego...
09/26/2018 ∙ by Xin Dang, et al. ∙ 0 ∙ share

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On mutual information estimation for mixed-pair random variables

We study the mutual information estimation for mixed-pair random variabl...
12/27/2018 ∙ by Aleksandr Beknazaryan, et al. ∙ 0 ∙ share

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Simulation-based inference methods for partially observed Markov model via the R package is2

Partially observed Markov process (POMP) models are powerful tools for t...
11/07/2018 ∙ by Duc Anh Doan, et al. ∙ 0 ∙ share

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Estimating Feature-Label Dependence Using Gini Distance Statistics

Identifying statistical dependence between the features and the label is...
06/05/2019 ∙ by Silu Zhang, et al. ∙ 0 ∙ share

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Depth-based Weighted Jackknife Empirical Likelihood for Non-smooth U-structure Equations

In many applications, parameters of interest are estimated by solving so...
06/16/2019 ∙ by Yongli Sang, et al. ∙ 0 ∙ share

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Jackknife Empirical Likelihood Approach for K-sample Tests

The categorical Gini correlation is an alternative measure of dependence...
08/01/2019 ∙ by Yongli Sang, et al. ∙ 0 ∙ share

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Empirical Likelihood Test for Diagonal Symmetry

Energy distance is a statistical distance between the distributions of r...
08/19/2019 ∙ by Yongli Sang, et al. ∙ 0 ∙ share

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Weakly smooth Langevin Monte Carlo using p-generalized Gaussian smoothing

Langevin Monte Carlo (LMC) is an iterative process for sampling from a d...
02/24/2020 ∙ by Anh Duc Doan, et al. ∙ 0 ∙ share

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Xin Dang

Featured Co-authors

Yixin Chen

Dao Nguyen

Yongli Sang

Hailin Sang

Yichuan Zhao

Aleksandr Beknazaryan

Zhi Xiao

Zhe Luo

Bo Zhong

Duc Anh Doan

Silu Zhang

A rank-based Cramér-von-Mises-type test for two samples

Robust and Efficient Boosting Method using the Conditional Risk

Jackknife Empirical Likelihood Methods for Gini Correlations and their Equality Testing

A new Gini correlation between quantitative and qualitative variables

On mutual information estimation for mixed-pair random variables

Simulation-based inference methods for partially observed Markov model via the R package is2

Estimating Feature-Label Dependence Using Gini Distance Statistics

Depth-based Weighted Jackknife Empirical Likelihood for Non-smooth U-structure Equations

Jackknife Empirical Likelihood Approach for K-sample Tests

Empirical Likelihood Test for Diagonal Symmetry

Weakly smooth Langevin Monte Carlo using p-generalized Gaussian smoothing