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Lianyan Fu & Luyang Zhang. (2024) Measures of conditional dependence for nonlinearity, asymmetry and beyond. Journal of Statistical Planning and Inference 232, pages 106165.
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Hongjian Shi, Mathias Drton & Fang Han. (2024) On Azadkia–Chatterjee’s conditional dependence coefficient. Bernoulli 30:2.
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Shulei Wang, Bo Yuan, T Tony Cai & Hongzhe Li. (2023) Phylogenetic association analysis with conditional rank correlation. Biometrika.
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Chenlu Ke, Wei Yang, Qingcong Yuan & Lu Li. (2023) Partial sufficient variable screening with categorical controls. Computational Statistics & Data Analysis 187, pages 107784.
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Ling-yue Zhang & Heng-jian Cui. (2023) Local Dependence Test Between Random Vectors Based on the Robust Conditional Spearman’s ρ and Kendall’s τ. Acta Mathematicae Applicatae Sinica, English Series 39:3, pages 491-510.
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Dingke Tang, Dehan Kong, Wenliang Pan & Linbo Wang. (2023) Ultra-High Dimensional Variable Selection for Doubly Robust Causal Inference. Biometrics 79:2, pages 903-914.
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Abdul-Nasah Soale. (2023) Projection expectile regression for sufficient dimension reduction. Computational Statistics & Data Analysis 180, pages 107666.
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Hengjian Cui, Yanyan Liu, Guangcai Mao & Jing Zhang. (2022) Model‐free conditional screening for ultrahigh‐dimensional survival data via conditional distance correlation. Biometrical Journal 65:3.
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Pascal Bianchi, Kevin Elgui & François Portier. (2023) Conditional independence testing via weighted partial copulas. Journal of Multivariate Analysis 193, pages 105120.
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Jihwan Oh, Changgee Chang & Qi Long. (2023) Accounting for technical noise in Bayesian graphical models of single-cell RNA-sequencing data. Biostatistics 24:1, pages 161-176.
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Ilmun Kim, Matey Neykov, Sivaraman Balakrishnan & Larry Wasserman. (2022) Local permutation tests for conditional independence. The Annals of Statistics 50:6.
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Dominic Edelmann & Jelle Goeman. (2022) A Regression Perspective on Generalized Distance Covariance and the Hilbert–Schmidt Independence Criterion. Statistical Science 37:4.
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Qingcong Yuan, Xianyan Chen, Chenlu Ke & Xiangrong Yin. (2022) Independence index sufficient variable screening for categorical responses. Computational Statistics & Data Analysis 174, pages 107530.
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Hongjie Ke, Zhao Ren, Jianfei Qi, Shuo Chen, George C Tseng, Zhenyao Ye & Tianzhou Ma. (2022) High-dimension to high-dimension screening for detecting genome-wide epigenetic and noncoding RNA regulators of gene expression. Bioinformatics 38:17, pages 4078-4087.
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Shubhadeep Chakraborty & Ali Shojaie. (2022) Nonparametric Causal Structure Learning in High Dimensions. Entropy 24:3, pages 351.
Crossref
Cheng Huang & Xiaoming Huo. (2022) A Statistically and Numerically Efficient Independence Test Based on Random Projections and Distance Covariance. Frontiers in Applied Mathematics and Statistics 7.
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Pengfei Liu, Xuejun Ma & Wang Zhou. (2020) HIGH-ORDER CONDITIONAL DISTANCE COVARIANCE WITH CONDITIONAL MUTUAL INDEPENDENCE. Probability in the Engineering and Informational Sciences 36:1, pages 126-143.
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Dag Tjøstheim, Håkon Otneim & Bård Støve. 2022. Statistical Modeling Using Local Gaussian Approximation. Statistical Modeling Using Local Gaussian Approximation 353 383 .
Mona Azadkia & Sourav Chatterjee. (2021) A simple measure of conditional dependence. The Annals of Statistics 49:6.
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Qiang Zhang, Wenliang Pan, Chengwei Li & Xueqin Wang. (2021) The conditional distance autocovariance function. Canadian Journal of Statistics 49:4, pages 1093-1114.
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Kai Xu & Mingxiang Cao. (2021) Distance-covariance-based tests for heteroscedasticity in nonlinear regressions. Science China Mathematics 64:10, pages 2327-2356.
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Cencheng Shen & Joshua T. Vogelstein. (2020) The exact equivalence of distance and kernel methods in hypothesis testing. AStA Advances in Statistical Analysis 105:3, pages 385-403.
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Lan Gao, Yingying Fan, Jinchi Lv & Qi-Man Shao. (2021) Asymptotic distributions of high-dimensional distance correlation inference. The Annals of Statistics 49:4.
Crossref
Xuehu Zhu, Jun Lu, Jun Zhang & Lixing Zhu. (2021) Testing for conditional independence: A groupwise dimension reduction‐based adaptive‐to‐model approach. Scandinavian Journal of Statistics 48:2, pages 549-576.
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Lei Fan. (2021) An ensemble variable selection method based on conditional mutual information. An ensemble variable selection method based on conditional mutual information.
Jianqing Fan, Yang Feng & Lucy Xia. (2020) A projection-based conditional dependence measure with applications to high-dimensional undirected graphical models. Journal of Econometrics 218:1, pages 119-139.
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Hunyong Cho, Joshua P. Zitovsky, Xinyi Li, Minxin Lu, Kushal Shah, John Sperger, Matthew C. B. Tsilimigras & Michael R. Kosorok. (2020) Comment: Diagnostics and Kernel-based Extensions for Linear Mixed Effects Models with Endogenous Covariates. Statistical Science 35:3.
Crossref
Fengli Song, Yurong Chen & Peng Lai. (2020) Conditional distance correlation screening for sparse ultrahigh-dimensional models. Applied Mathematical Modelling 81, pages 232-252.
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Chun Li & Xiaodan Fan. (2019) On nonparametric conditional independence tests for continuous variables. WIREs Computational Statistics 12:3.
Crossref
Jun Lu & Lu Lin. (2017) Model-free conditional screening via conditional distance correlation. Statistical Papers 61:1, pages 225-244.
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Xinyi Xu & Jingxiao Zhang. (2019) Groupwise sufficient dimension reduction via conditional distance clustering. Metrika 83:2, pages 217-242.
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Yeqing Zhou, Jingyuan Liu & Liping Zhu. (2020) Test for conditional independence with application to conditional screening. Journal of Multivariate Analysis 175, pages 104557.
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Dominic Edelmann, Konstantinos Fokianos & Maria Pitsillou. (2018) An Updated Literature Review of Distance Correlation and Its Applications to Time Series. International Statistical Review 87:2, pages 237-262.
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Qingyang Zhang. (2019) Independence test for large sparse contingency tables based on distance correlation. Statistics & Probability Letters 148, pages 17-22.
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Joshua T Vogelstein, Eric W Bridgeford, Qing Wang, Carey E Priebe, Mauro Maggioni & Cencheng Shen. (2019) Discovering and deciphering relationships across disparate data modalities. eLife 8.
Crossref
Qingyang Zhang & Jian Tinker. (2019) Testing conditional independence and homogeneity in large sparse three‐way tables using conditional distance covariance. Stat 8:1.
Crossref
J. Runge. (2018) Causal network reconstruction from time series: From theoretical assumptions to practical estimation. Chaos: An Interdisciplinary Journal of Nonlinear Science 28:7.
Crossref
Yi Liu & Qihua Wang. (2017) Model-free feature screening for ultrahigh-dimensional data conditional on some variables. Annals of the Institute of Statistical Mathematics 70:2, pages 283-301.
Crossref
Guozhu Dong & Sanjeev Bhatta. (2017) Subpopulation-Wise Conditional Correlation Modeling and Analysis. Subpopulation-Wise Conditional Correlation Modeling and Analysis.
Gábor J. Székely & Maria L. Rizzo. (2017) The Energy of Data. Annual Review of Statistics and Its Application 4:1, pages 447-479.
Crossref
Wenliang Pan, Xueqin Wang, Canhong Wen, Martin Styner & Hongtu Zhu. 2017. Information Processing in Medical Imaging. Information Processing in Medical Imaging 41 52 .
Trevor Park, Xiaofeng Shao & Shun Yao. (2015) Partial martingale difference correlation. Electronic Journal of Statistics 9:1.
Crossref
Amelie Charles & Olivier Darné. (2022) Forecasting Macroeconomic Time Series Using Sparse Random Forest Models. SSRN Electronic Journal.
Crossref

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