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Gaussian Approximations for the $k$th coordinate of sums of random vectors

Autor: Ding, Yixi, Li, Qizhai, Shi, Yuke, Zhang, Wei

We consider the problem of Gaussian approximation for the $\kappa$th coordinate of a sum of high-dimensional random vectors. Such a problem has been studied previously for $\kappa=1$ (i.e., maxima). However, in many applications, a general $\kappa\ge

Externí odkaz: http://arxiv.org/abs/2408.03039

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Functional knockoffs selection with applications to functional data analysis in high dimensions

Autor: Qiao, Xinghao, Long, Mingya, Li, Qizhai

The knockoffs is a recently proposed powerful framework that effectively controls the false discovery rate (FDR) for variable selection. However, none of the existing knockoff solutions are directly suited to handle multivariate or high-dimensional f

Externí odkaz: http://arxiv.org/abs/2406.18189

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A family of Chatterjee's correlation coefficients and their properties

Autor: Gao, Muhong, Li, Qizhai

Quantifying the strength of functional dependence between random scalars $X$ and $Y$ is an important statistical problem. While many existing correlation coefficients excel in identifying linear or monotone functional dependence, they fall short in c

Externí odkaz: http://arxiv.org/abs/2403.17670

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The Cauchy Combination Test under Arbitrary Dependence Structures

Autor: Long, Mingya, Li, Zhengbang, Zhang, Wei, Li, Qizhai

Aggregating multiple effects is often encountered in large-scale data analysis where the fraction of significant effects is generally small. Many existing methods cannot handle it effectively because of lack of computational accuracy for small p-valu

Externí odkaz: http://arxiv.org/abs/2107.06040

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Distance-based regression analysis for measuring associations

Autor: Shi, Yuke, Zhang, Wei, Liu, Aiyi, Li, Qizhai

Distance-based regression model, as a nonparametric multivariate method, has been widely used to detect the association between variations in a distance or dissimilarity matrix for outcomes and predictor variables of interest in genetic association s

Externí odkaz: http://arxiv.org/abs/2105.10145

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An Imputation-Consistency Algorithm for High-Dimensional Missing Data Problems and Beyond

Autor: Liang, Faming, Jia, Bochao, Xue, Jingnan, Li, Qizhai, Luo, Ye

Missing data are frequently encountered in high-dimensional problems, but they are usually difficult to deal with using standard algorithms, such as the expectation-maximization (EM) algorithm and its variants. To tackle this difficulty, some problem

Externí odkaz: http://arxiv.org/abs/1802.02251

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