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Journal of the American Statistical Association Volume 116, 2021 - Issue 535
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Theory and Methods

Metropolized Knockoff Sampling

Stephen Batesa Department of Statistics, Stanford University, Stanford, CA; View further author information
,
Emmanuel Candèsb Department of Mathematics and Statistics, Stanford University, Stanford, CA; View further author information
,
Lucas Jansonc Department of Statistics, Harvard University, Cambridge, MAView further author information
&
Wenshuo Wangc Department of Statistics, Harvard University, Cambridge, MACorrespondence[email protected]
View further author information
Pages 1413-1427 | Received 05 Mar 2019, Accepted 30 Jan 2020, Published online: 17 Mar 2020

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Ka Wai Tsang, Fugee Tsung & Zhihao Xu. (2023) Knockoff procedure for false discovery rate control in high-dimensional data streams. Journal of Applied Statistics 50:14, pages 2970-2983.
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Chenguang Dai, Buyu Lin, Xin Xing & Jun S. Liu. (2023) False Discovery Rate Control via Data Splitting. Journal of the American Statistical Association 118:544, pages 2503-2520.
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Chenguang Dai, Buyu Lin, Xin Xing & Jun S. Liu. (2023) A Scale-Free Approach for False Discovery Rate Control in Generalized Linear Models. Journal of the American Statistical Association 118:543, pages 1551-1565.
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Alejandro Román Vásquez, José Ulises Márquez Urbina, Graciela González Farías & Gabriel Escarela. (2023) Controlling the false discovery rate by a Latent Gaussian Copula Knockoff procedure. Computational Statistics 39:3, pages 1435-1458.
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Manuela R. Zimmermann, Mark Baillie, Matthias Kormaksson, David Ohlssen & Konstantinos Sechidis. (2024) All that Glitters Is not Gold: Type‐I Error Controlled Variable Selection from Clinical Trial Data. Clinical Pharmacology & Therapeutics 115:4, pages 774-785.
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Adel Javanmard & Mohammad Mehrabi. (2024) GRASP: a goodness-of-fit test for classification learning. Journal of the Royal Statistical Society Series B: Statistical Methodology 86:1, pages 215-245.
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Zhimei Ren & Rina Foygel Barber. (2024) Derandomised knockoffs: leveraging e -values for false discovery rate control . Journal of the Royal Statistical Society Series B: Statistical Methodology 86:1, pages 122-154.
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Gianna Serafina Monti & Peter Filzmoser. (2022) A robust knockoff filter for sparse regression analysis of microbiome compositional data. Computational Statistics 39:1, pages 271-288.
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Julien Hédou, Ivana Marić, Grégoire Bellan, Jakob Einhaus, Dyani K. Gaudillière, Francois-Xavier Ladant, Franck Verdonk, Ina A. Stelzer, Dorien Feyaerts, Amy S. Tsai, Edward A. Ganio, Maximilian Sabayev, Joshua Gillard, Jonas Amar, Amelie Cambriel, Tomiko T. Oskotsky, Alennie Roldan, Jonathan L. Golob, Marina Sirota, Thomas A. Bonham, Masaki Sato, Maïgane Diop, Xavier Durand, Martin S. Angst, David K. Stevenson, Nima Aghaeepour, Andrea Montanari & Brice Gaudillière. (2024) Discovery of sparse, reliable omic biomarkers with Stabl. Nature Biotechnology.
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Emanuela Dreassi, Fabrizio Leisen, Luca Pratelli & Pietro Rigo. (2024) Generating knockoffs via conditional independence. Electronic Journal of Statistics 18:1.
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Ran Cui, Roy A. Elzur, Masahiro Kanai, Jacob C. Ulirsch, Omer Weissbrod, Mark J. Daly, Benjamin M. Neale, Zhou Fan & Hilary K. Finucane. (2023) Improving fine-mapping by modeling infinitesimal effects. Nature Genetics 56:1, pages 162-169.
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Ran Dai & Cheng Zheng. (2023) False Discovery Rate-Controlled Multiple Testing for Union Null Hypotheses: A Knockoff-Based Approach. Biometrics 79:4, pages 3497-3509.
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Panxu Yuan, Yinfei Kong & Gaorong Li. (2023) FDR control and power analysis for high-dimensional logistic regression via StabKoff. Statistical Papers.
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Zhimei Ren & Emmanuel Candès. (2023) Knockoffs with side information. The Annals of Applied Statistics 17:2.
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Arun Srinivasan, Lingzhou Xue & Xiang Zhan. (2023) Identification of microbial features in multivariate regression under false discovery rate control. Computational Statistics & Data Analysis 181, pages 107621.
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Kristin Blesch, David S. Watson & Marvin N. Wright. (2023) Conditional feature importance for mixed data. AStA Advances in Statistical Analysis.
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Patrizia Berti, Emanuela Dreassi, Fabrizio Leisen, Luca Pratelli & Pietro Rigo. (2023) New perspectives on knockoffs construction. Journal of Statistical Planning and Inference 223, pages 1-14.
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Zhenzhong Wang, Zhengyuan Zhu & Cindy Yu. (2023) Variable Selection in Macroeconomic Forecasting with Many Predictors. Econometrics and Statistics.
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Kristin Blesch, Marvin N. Wright & David Watson. 2023. Explainable Artificial Intelligence. Explainable Artificial Intelligence 131 146 .
Christoph Molnar, Timo Freiesleben, Gunnar König, Julia Herbinger, Tim Reisinger, Giuseppe Casalicchio, Marvin N. Wright & Bernd Bischl. 2023. Explainable Artificial Intelligence. Explainable Artificial Intelligence 456 479 .
Domen Vreš & Marko Robnik-Šikonja. (2022) Preventing deception with explanation methods using focused sampling. Data Mining and Knowledge Discovery.
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S Li, M Sesia, Y Romano, E Candès & C Sabatti. (2022) Searching for robust associations with a multi-environment knockoff filter. Biometrika 109:3, pages 611-629.
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Wenshuo Wang & Lucas Janson. (2022) A high-dimensional power analysis of the conditional randomization test and knockoffs. Biometrika 109:3, pages 631-645.
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Eugene Katsevich & Aaditya Ramdas. (2022) On the power of conditional independence testing under model-X. Electronic Journal of Statistics 16:2.
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David Mary & Etienne Roquain. (2022) Semi-supervised multiple testing. Electronic Journal of Statistics 16:2.
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Mohammadali Olyaei, Ardeshir Ebtehaj & Jiarong Hong. (2022) Optical Detection of Marine Debris Using Deep Knockoff. IEEE Transactions on Geoscience and Remote Sensing 60, pages 1-12.
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David S. Watson. 2022. The 2021 Yearbook of the Digital Ethics Lab. The 2021 Yearbook of the Digital Ethics Lab 133 155 .
Konstantinos Sechidis, Matthias Kormaksson & David Ohlssen. (2021) Using knockoffs for controlled predictive biomarker identification. Statistics in Medicine 40:25, pages 5453-5473.
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Zifan Zhu, Yingying Fan, Yinfei Kong, Jinchi Lv & Fengzhu Sun. (2021) DeepLINK: Deep learning inference using knockoffs with applications to genomics. Proceedings of the National Academy of Sciences 118:36.
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Arun Srinivasan, Lingzhou Xue & Xiang Zhan. (2020) Compositional knockoff filter for high‐dimensional regression analysis of microbiome data. Biometrics 77:3, pages 984-995.
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David S. Watson & Marvin N. Wright. (2021) Testing conditional independence in supervised learning algorithms. Machine Learning 110:8, pages 2107-2129.
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Dongming Huang & Lucas Janson. (2020) Relaxing the assumptions of knockoffs by conditioning. The Annals of Statistics 48:5.
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Stephen BatesMatteo Sesia, Chiara SabattiEmmanuel Candès. (2020) Causal inference in genetic trio studies. Proceedings of the National Academy of Sciences 117:39, pages 24117-24126.
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