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Statistics Jul 2019
<!DOCTYPE html> <html lang="en"> <head> <title>Statistics Jul 2019</title> <meta name="viewport" content="width=device-width, initial-scale=1"> <link rel="apple-touch-icon" sizes="180x180" href="/static/browse/0.3.4/images/icons/apple-touch-icon.png"> <link rel="icon" type="image/png" sizes="32x32" href="/static/browse/0.3.4/images/icons/favicon-32x32.png"> <link rel="icon" type="image/png" sizes="16x16" href="/static/browse/0.3.4/images/icons/favicon-16x16.png"> <link rel="manifest" href="/static/browse/0.3.4/images/icons/site.webmanifest"> <link rel="mask-icon" href="/static/browse/0.3.4/images/icons/safari-pinned-tab.svg" color="#5bbad5"> <meta name="msapplication-TileColor" content="#da532c"> <meta name="theme-color" content="#ffffff"> <link rel="stylesheet" type="text/css" media="screen" href="/static/browse/0.3.4/css/arXiv.css?v=20241206" /> <link rel="stylesheet" type="text/css" media="print" href="/static/browse/0.3.4/css/arXiv-print.css?v=20200611" /> <link rel="stylesheet" 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class='morefewer'>Showing up to 50 entries per page: <a href=/list/stat/2019-07?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat/2019-07?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat/2019-07?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <dt> <a name='item1'>[1]</a> <a href ="/abs/1907.00004" title="Abstract" id="1907.00004"> arXiv:1907.00004 </a> [<a href="/pdf/1907.00004" title="Download PDF" id="pdf-1907.00004" aria-labelledby="pdf-1907.00004">pdf</a>, <a href="/format/1907.00004" title="Other formats" id="oth-1907.00004" aria-labelledby="oth-1907.00004">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Test for parameter change in the presence of outliers: the density power divergence based approach </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Song,+J">Junmo Song</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Kang,+J">Jiwon Kang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 26 pages, 2 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item2'>[2]</a> <a href ="/abs/1907.00020" title="Abstract" id="1907.00020"> arXiv:1907.00020 </a> [<a href="/pdf/1907.00020" title="Download PDF" id="pdf-1907.00020" aria-labelledby="pdf-1907.00020">pdf</a>, <a href="/format/1907.00020" title="Other formats" id="oth-1907.00020" aria-labelledby="oth-1907.00020">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Training individually fair ML models with Sensitive Subspace Robustness </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Yurochkin,+M">Mikhail Yurochkin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bower,+A">Amanda Bower</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sun,+Y">Yuekai Sun</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> ICLR 2020 (spotlight) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item3'>[3]</a> <a href ="/abs/1907.00030" title="Abstract" id="1907.00030"> arXiv:1907.00030 </a> [<a href="/pdf/1907.00030" title="Download PDF" id="pdf-1907.00030" aria-labelledby="pdf-1907.00030">pdf</a>, <a href="/format/1907.00030" title="Other formats" id="oth-1907.00030" aria-labelledby="oth-1907.00030">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Buhai,+R">Rares-Darius Buhai</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Halpern,+Y">Yoni Halpern</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kim,+Y">Yoon Kim</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Risteski,+A">Andrej Risteski</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sontag,+D">David Sontag</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 22 pages, to appear at ICML 2020 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item4'>[4]</a> <a href ="/abs/1907.00032" title="Abstract" id="1907.00032"> arXiv:1907.00032 </a> [<a href="/pdf/1907.00032" title="Download PDF" id="pdf-1907.00032" aria-labelledby="pdf-1907.00032">pdf</a>, <a href="/format/1907.00032" title="Other formats" id="oth-1907.00032" aria-labelledby="oth-1907.00032">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Cross-product Penalized Component Analysis (XCAN) </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Camacho,+J">Jos茅 Camacho</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Acar,+E">Evrim Acar</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Rasmussen,+M+A">Morten A. Rasmussen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bro,+R">Rasmus Bro</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Chemometrics and Intelligent Laboratory Systems, 2020, 203: 104038- </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/1907.00057" title="Abstract" id="1907.00057"> arXiv:1907.00057 </a> [<a href="/pdf/1907.00057" title="Download PDF" id="pdf-1907.00057" aria-labelledby="pdf-1907.00057">pdf</a>, <a href="/format/1907.00057" title="Other formats" id="oth-1907.00057" aria-labelledby="oth-1907.00057">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Fast and Exact Simulation of Multivariate Normal and Wishart Random Variables with Box Constraints </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Koch,+H">Hillary Koch</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bopp,+G+P">Gregory P. Bopp</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> There is an error in the the technical proofs for the proposed algorithms' validity. While the proposed algorithms can in many cases produce approximate draws from the described target distributions, they do not produce exact draws </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span> </div> </div> </dd> <dt> <a name='item6'>[6]</a> <a href ="/abs/1907.00063" title="Abstract" id="1907.00063"> arXiv:1907.00063 </a> [<a href="/pdf/1907.00063" title="Download PDF" id="pdf-1907.00063" aria-labelledby="pdf-1907.00063">pdf</a>, <a href="/format/1907.00063" title="Other formats" id="oth-1907.00063" aria-labelledby="oth-1907.00063">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayesian Nonparametric Boolean Factor Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Rukat,+T">Tammo Rukat</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yau,+C">Christopher Yau</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Presented at the 2018 NeurIPS Workshop on Bayesian Nonparametrics </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item7'>[7]</a> <a href ="/abs/1907.00085" title="Abstract" id="1907.00085"> arXiv:1907.00085 </a> [<a href="/pdf/1907.00085" title="Download PDF" id="pdf-1907.00085" aria-labelledby="pdf-1907.00085">pdf</a>, <a href="/format/1907.00085" title="Other formats" id="oth-1907.00085" aria-labelledby="oth-1907.00085">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Large-scale inference with block structure </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Kou,+J">Jiyao Kou</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Walther,+G">Guenther Walther</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item8'>[8]</a> <a href ="/abs/1907.00093" title="Abstract" id="1907.00093"> arXiv:1907.00093 </a> [<a href="/pdf/1907.00093" title="Download PDF" id="pdf-1907.00093" aria-labelledby="pdf-1907.00093">pdf</a>, <a href="/format/1907.00093" title="Other formats" id="oth-1907.00093" aria-labelledby="oth-1907.00093">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Data integration for high-resolution, continental-scale estimation of air pollution concentrations </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Thomas,+M+L">Matthew L. Thomas</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Shaddick,+G">Gavin Shaddick</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Simpson,+D">Daniel Simpson</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=de+Hoogh,+K">Kees de Hoogh</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zidek,+J+V">James V. Zidek</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/1907.00111" title="Abstract" id="1907.00111"> arXiv:1907.00111 </a> [<a href="/pdf/1907.00111" title="Download PDF" id="pdf-1907.00111" aria-labelledby="pdf-1907.00111">pdf</a>, <a href="/format/1907.00111" title="Other formats" id="oth-1907.00111" aria-labelledby="oth-1907.00111">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> An Intrinsic Geometrical Approach for Statistical Process Control of Surface and Manifold Data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Zhao,+X">Xueqi Zhao</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=del+Castillo,+E">Enrique del Castillo</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item10'>[10]</a> <a href ="/abs/1907.00113" title="Abstract" id="1907.00113"> arXiv:1907.00113 </a> [<a href="/pdf/1907.00113" title="Download PDF" id="pdf-1907.00113" aria-labelledby="pdf-1907.00113">pdf</a>, <a href="/format/1907.00113" title="Other formats" id="oth-1907.00113" aria-labelledby="oth-1907.00113">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Learning Markov models via low-rank optimization </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Zhu,+Z">Ziwei Zhu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+X">Xudong Li</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+M">Mengdi Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhang,+A">Anru Zhang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 52 pages, 4 figures. arXiv admin note: text overlap with <a href="https://arxiv.org/abs/1804.00795" data-arxiv-id="1804.00795" class="link-https">arXiv:1804.00795</a> </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/1907.00161" title="Abstract" id="1907.00161"> arXiv:1907.00161 </a> [<a href="/pdf/1907.00161" title="Download PDF" id="pdf-1907.00161" aria-labelledby="pdf-1907.00161">pdf</a>, <a href="/format/1907.00161" title="Other formats" id="oth-1907.00161" aria-labelledby="oth-1907.00161">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> trialr: Bayesian Clinical Trial Designs in R and Stan </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Brock,+K">Kristian Brock</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span>; Applications (stat.AP); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item12'>[12]</a> <a href ="/abs/1907.00196" title="Abstract" id="1907.00196"> arXiv:1907.00196 </a> [<a href="/pdf/1907.00196" title="Download PDF" id="pdf-1907.00196" aria-labelledby="pdf-1907.00196">pdf</a>, <a href="/format/1907.00196" title="Other formats" id="oth-1907.00196" aria-labelledby="oth-1907.00196">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Statistical estimation of the Kullback-Leibler divergence </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Bulinski,+A">Alexander Bulinski</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Dimitrov,+D">Denis Dimitrov</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span> </div> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/1907.00241" title="Abstract" id="1907.00241"> arXiv:1907.00241 </a> [<a href="/pdf/1907.00241" title="Download PDF" id="pdf-1907.00241" aria-labelledby="pdf-1907.00241">pdf</a>, <a href="/format/1907.00241" title="Other formats" id="oth-1907.00241" aria-labelledby="oth-1907.00241">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Identification In Missing Data Models Represented By Directed Acyclic Graphs </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Bhattacharya,+R">Rohit Bhattacharya</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Nabi,+R">Razieh Nabi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Shpitser,+I">Ilya Shpitser</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Robins,+J+M">James M. Robins</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 16 pages, published in proceedings of 35th Conference on Uncertainty in Artificial Intelligence (UAI 2019) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item14'>[14]</a> <a href ="/abs/1907.00287" title="Abstract" id="1907.00287"> arXiv:1907.00287 </a> [<a href="/pdf/1907.00287" title="Download PDF" id="pdf-1907.00287" aria-labelledby="pdf-1907.00287">pdf</a>, <a href="/format/1907.00287" title="Other formats" id="oth-1907.00287" aria-labelledby="oth-1907.00287">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Estimating Treatment Effect under Additive Hazards Models with High-dimensional Covariates </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Hou,+J">Jue Hou</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bradic,+J">Jelena Bradic</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Xu,+R">Ronghui Xu</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Journal of the American Statistical Association 118(541) 327-342 (2021) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Quantitative Methods (q-bio.QM); Applications (stat.AP); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item15'>[15]</a> <a href ="/abs/1907.00288" title="Abstract" id="1907.00288"> arXiv:1907.00288 </a> [<a href="/pdf/1907.00288" title="Download PDF" id="pdf-1907.00288" aria-labelledby="pdf-1907.00288">pdf</a>, <a href="/format/1907.00288" title="Other formats" id="oth-1907.00288" aria-labelledby="oth-1907.00288">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A New Lower Bound for Kullback-Leibler Divergence Based on Hammersley-Chapman-Robbins Bound </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Nishiyama,+T">Tomohiro Nishiyama</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 8 pages, 3 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Information Theory (cs.IT); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item16'>[16]</a> <a href ="/abs/1907.00296" title="Abstract" id="1907.00296"> arXiv:1907.00296 </a> [<a href="/pdf/1907.00296" title="Download PDF" id="pdf-1907.00296" aria-labelledby="pdf-1907.00296">pdf</a>, <a href="/format/1907.00296" title="Other formats" id="oth-1907.00296" aria-labelledby="oth-1907.00296">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Geodesic Distance Estimation with Spherelets </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Li,+D">Didong Li</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Dunson,+D+B">David B Dunson</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item17'>[17]</a> <a href ="/abs/1907.00307" title="Abstract" id="1907.00307"> arXiv:1907.00307 </a> [<a href="/pdf/1907.00307" title="Download PDF" id="pdf-1907.00307" aria-labelledby="pdf-1907.00307">pdf</a>, <a href="/format/1907.00307" title="Other formats" id="oth-1907.00307" aria-labelledby="oth-1907.00307">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Outlier-robust Kalman filters with mixture correntropy </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+H">Hongwei Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhang,+W">Wei Zhang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zuo,+J">Junyi Zuo</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+H">Heping Wang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Applications (stat.AP) </div> </div> </dd> <dt> <a name='item18'>[18]</a> <a href ="/abs/1907.00345" title="Abstract" id="1907.00345"> arXiv:1907.00345 </a> [<a href="/pdf/1907.00345" title="Download PDF" id="pdf-1907.00345" aria-labelledby="pdf-1907.00345">pdf</a>, <a href="/format/1907.00345" title="Other formats" id="oth-1907.00345" aria-labelledby="oth-1907.00345">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Frequentist performances of Bayesian prediction intervals for random-effects meta-analysis </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Hamaguchi,+Y">Yuta Hamaguchi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Noma,+H">Hisashi Noma</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Nagashima,+K">Kengo Nagashima</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yamada,+T">Tomohide Yamada</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Furukawa,+T+A">Toshi A. Furukawa</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 23 pages, 4 figures, 1 table </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Biom J 2021;63(2):394-405 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item19'>[19]</a> <a href ="/abs/1907.00389" title="Abstract" id="1907.00389"> arXiv:1907.00389 </a> [<a href="/pdf/1907.00389" title="Download PDF" id="pdf-1907.00389" aria-labelledby="pdf-1907.00389">pdf</a>, <a href="/format/1907.00389" title="Other formats" id="oth-1907.00389" aria-labelledby="oth-1907.00389">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Coupling techniques for nonlinear ensemble filtering </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Spantini,+A">Alessio Spantini</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Baptista,+R">Ricardo Baptista</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Marzouk,+Y">Youssef Marzouk</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> To appear in SIAM Review. 47 pages, 18 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Computation (stat.CO); Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item20'>[20]</a> <a href ="/abs/1907.00399" title="Abstract" id="1907.00399"> arXiv:1907.00399 </a> [<a href="/pdf/1907.00399" title="Download PDF" id="pdf-1907.00399" aria-labelledby="pdf-1907.00399">pdf</a>, <a href="/format/1907.00399" title="Other formats" id="oth-1907.00399" aria-labelledby="oth-1907.00399">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bounding Causes of Effects with Mediators </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Dawid,+P">Philip Dawid</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Humphreys,+M">Macartan Humphreys</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Musio,+M">Monica Musio</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 23 pages, 2 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Econometrics (econ.EM) </div> </div> </dd> <dt> <a name='item21'>[21]</a> <a href ="/abs/1907.00502" title="Abstract" id="1907.00502"> arXiv:1907.00502 </a> [<a href="/pdf/1907.00502" title="Download PDF" id="pdf-1907.00502" aria-labelledby="pdf-1907.00502">pdf</a>, <a href="/format/1907.00502" title="Other formats" id="oth-1907.00502" aria-labelledby="oth-1907.00502">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Wave-shape oscillatory model for nonstationary periodic time series analysis </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Lin,+Y">Yu-Ting Lin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Malik,+J">John Malik</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wu,+H">Hau-Tieng Wu</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 35 pages, 15 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item22'>[22]</a> <a href ="/abs/1907.00519" title="Abstract" id="1907.00519"> arXiv:1907.00519 </a> [<a href="/pdf/1907.00519" title="Download PDF" id="pdf-1907.00519" aria-labelledby="pdf-1907.00519">pdf</a>, <a href="/format/1907.00519" title="Other formats" id="oth-1907.00519" aria-labelledby="oth-1907.00519">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Transformed Naive Ratio and Product Based Estimators for Estimating Population Mode in Simple Random Sampling </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kumar,+S">Sanjay Kumar</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Tiwari,+N">Nirmal Tiwari</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 25 pages, 11 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item23'>[23]</a> <a href ="/abs/1907.00586" title="Abstract" id="1907.00586"> arXiv:1907.00586 </a> [<a href="/pdf/1907.00586" title="Download PDF" id="pdf-1907.00586" aria-labelledby="pdf-1907.00586">pdf</a>, <a href="/format/1907.00586" title="Other formats" id="oth-1907.00586" aria-labelledby="oth-1907.00586">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Kernel Stein Test for Comparing Latent Variable Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kanagawa,+H">Heishiro Kanagawa</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Jitkrittum,+W">Wittawat Jitkrittum</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mackey,+L">Lester Mackey</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Fukumizu,+K">Kenji Fukumizu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gretton,+A">Arthur Gretton</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> This is a pre-copyedited, author-produced version of an article accepted for publication in The Journal of the Royal Statistical Society Series: B following peer review </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item24'>[24]</a> <a href ="/abs/1907.00603" title="Abstract" id="1907.00603"> arXiv:1907.00603 </a> [<a href="/pdf/1907.00603" title="Download PDF" id="pdf-1907.00603" aria-labelledby="pdf-1907.00603">pdf</a>, <a href="/format/1907.00603" title="Other formats" id="oth-1907.00603" aria-labelledby="oth-1907.00603">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Applying Meta-Analytic-Predictive Priors with the R Bayesian evidence synthesis tools </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Weber,+S">Sebastian Weber</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Li,+Y">Yue Li</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Seaman,+J">John Seaman</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kakizume,+T">Tomoyuki Kakizume</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Schmidli,+H">Heinz Schmidli</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 27 pages, 3 figures, RBesT R package on CRAN <a href="https://cran.r-project.org/package=RBesT" rel="external noopener nofollow" class="link-external link-https">this https URL</a> </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item25'>[25]</a> <a href ="/abs/1907.00668" title="Abstract" id="1907.00668"> arXiv:1907.00668 </a> [<a href="/pdf/1907.00668" title="Download PDF" id="pdf-1907.00668" aria-labelledby="pdf-1907.00668">pdf</a>, <a href="/format/1907.00668" title="Other formats" id="oth-1907.00668" aria-labelledby="oth-1907.00668">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Power Lindley distribution and software metrics </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Khalleefah,+M">Mohammed Khalleefah</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Ostrovska,+S">Sofiya Ostrovska</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Turan,+M">Mehmet Turan</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 15 pages, 3 figures,4 tables </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Probability (math.PR) </div> </div> </dd> <dt> <a name='item26'>[26]</a> <a href ="/abs/1907.00686" title="Abstract" id="1907.00686"> arXiv:1907.00686 </a> [<a href="/pdf/1907.00686" title="Download PDF" id="pdf-1907.00686" aria-labelledby="pdf-1907.00686">pdf</a>, <a href="/format/1907.00686" title="Other formats" id="oth-1907.00686" aria-labelledby="oth-1907.00686">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Sparse regular variation </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Nicolas,+M">Meyer Nicolas</a> (LPSM (UMR\_8001)), <a href="https://arxiv.org/search/stat?searchtype=author&query=Wintenberger,+O">Olivier Wintenberger</a> (LPSM (UMR\_8001))</div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Statistics Theory (math.ST) </div> </div> </dd> <dt> <a name='item27'>[27]</a> <a href ="/abs/1907.00723" title="Abstract" id="1907.00723"> arXiv:1907.00723 </a> [<a href="/pdf/1907.00723" title="Download PDF" id="pdf-1907.00723" aria-labelledby="pdf-1907.00723">pdf</a>, <a href="/format/1907.00723" title="Other formats" id="oth-1907.00723" aria-labelledby="oth-1907.00723">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A greedy algorithm for sparse precision matrix approximation </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Lv,+D">Didi Lv</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Zhang,+X">Xiaoqun Zhang</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span> </div> </div> </dd> <dt> <a name='item28'>[28]</a> <a href ="/abs/1907.00786" title="Abstract" id="1907.00786"> arXiv:1907.00786 </a> [<a href="/pdf/1907.00786" title="Download PDF" id="pdf-1907.00786" aria-labelledby="pdf-1907.00786">pdf</a>, <a href="/format/1907.00786" title="Other formats" id="oth-1907.00786" aria-labelledby="oth-1907.00786">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> State-of-the-art in selection of variables and functional forms in multivariable analysis -- outstanding issues </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Sauerbrei,+W">Willi Sauerbrei</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Perperoglou,+A">Aris Perperoglou</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Schmid,+M">Matthias Schmid</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Abrahamowicz,+M">Michal Abrahamowicz</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Becher,+H">Heiko Becher</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Binder,+H">Harald Binder</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dunkler,+D">Daniela Dunkler</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Harrell,+F+E">Frank E. Harrell Jr</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Royston,+P">Patrick Royston</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Heinze,+G">Georg Heinze</a> (for TG2 of the STRATOS initiative)</div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item29'>[29]</a> <a href ="/abs/1907.00825" title="Abstract" id="1907.00825"> arXiv:1907.00825 </a> [<a href="/pdf/1907.00825" title="Download PDF" id="pdf-1907.00825" aria-labelledby="pdf-1907.00825">pdf</a>, <a href="/format/1907.00825" title="Other formats" id="oth-1907.00825" aria-labelledby="oth-1907.00825">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Time-to-Event Prediction with Neural Networks and Cox Regression </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kvamme,+H">H氓vard Kvamme</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Borgan,+%C3%98">脴rnulf Borgan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Scheel,+I">Ida Scheel</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Journal of Machine Learning Research, 20(129):1-30, 2019 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item30'>[30]</a> <a href ="/abs/1907.00846" title="Abstract" id="1907.00846"> arXiv:1907.00846 </a> [<a href="/pdf/1907.00846" title="Download PDF" id="pdf-1907.00846" aria-labelledby="pdf-1907.00846">pdf</a>, <a href="/format/1907.00846" title="Other formats" id="oth-1907.00846" aria-labelledby="oth-1907.00846">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> ICU Disparnumerophobia and Triskaidekaphobia: The 'Irrational Care Unit'? </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Ercole,+A">Ari Ercole</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item31'>[31]</a> <a href ="/abs/1907.00865" title="Abstract" id="1907.00865"> arXiv:1907.00865 </a> [<a href="/pdf/1907.00865" title="Download PDF" id="pdf-1907.00865" aria-labelledby="pdf-1907.00865">pdf</a>, <a href="/format/1907.00865" title="Other formats" id="oth-1907.00865" aria-labelledby="oth-1907.00865">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Farquhar,+S">Sebastian Farquhar</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Osborne,+M">Michael Osborne</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gal,+Y">Yarin Gal</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> AI Stats, PMLR 108:1352-1362, 2020 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item32'>[32]</a> <a href ="/abs/1907.00914" title="Abstract" id="1907.00914"> arXiv:1907.00914 </a> [<a href="/pdf/1907.00914" title="Download PDF" id="pdf-1907.00914" aria-labelledby="pdf-1907.00914">pdf</a>, <a href="/format/1907.00914" title="Other formats" id="oth-1907.00914" aria-labelledby="oth-1907.00914">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> ensr: R Package for Simultaneous Selection of Elastic Net Tuning Parameters </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=DeWitt,+P+E">Peter E. DeWitt</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bennett,+T+D">Tellen D. Bennett</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span> </div> </div> </dd> <dt> <a name='item33'>[33]</a> <a href ="/abs/1907.00927" title="Abstract" id="1907.00927"> arXiv:1907.00927 </a> [<a href="/pdf/1907.00927" title="Download PDF" id="pdf-1907.00927" aria-labelledby="pdf-1907.00927">pdf</a>, <a href="/format/1907.00927" title="Other formats" id="oth-1907.00927" aria-labelledby="oth-1907.00927">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Unified Approach to Robust Mean Estimation </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Prasad,+A">Adarsh Prasad</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Balakrishnan,+S">Sivaraman Balakrishnan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ravikumar,+P">Pradeep Ravikumar</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 51 pages, 6 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Artificial Intelligence (cs.AI); Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item34'>[34]</a> <a href ="/abs/1907.01003" title="Abstract" id="1907.01003"> arXiv:1907.01003 </a> [<a href="/pdf/1907.01003" title="Download PDF" id="pdf-1907.01003" aria-labelledby="pdf-1907.01003">pdf</a>, <a href="/format/1907.01003" title="Other formats" id="oth-1907.01003" aria-labelledby="oth-1907.01003">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Accurate, reliable and fast robustness evaluation </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Brendel,+W">Wieland Brendel</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Rauber,+J">Jonas Rauber</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=K%C3%BCmmerer,+M">Matthias K眉mmerer</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ustyuzhaninov,+I">Ivan Ustyuzhaninov</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Bethge,+M">Matthias Bethge</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted at the 2019 Conference on Neural Information Processing Systems </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Cryptography and Security (cs.CR); Computer Vision and Pattern Recognition (cs.CV); Machine Learning (cs.LG); Neural and Evolutionary Computing (cs.NE) </div> </div> </dd> <dt> <a name='item35'>[35]</a> <a href ="/abs/1907.01068" title="Abstract" id="1907.01068"> arXiv:1907.01068 </a> [<a href="/pdf/1907.01068" title="Download PDF" id="pdf-1907.01068" aria-labelledby="pdf-1907.01068">pdf</a>, <a href="/format/1907.01068" title="Other formats" id="oth-1907.01068" aria-labelledby="oth-1907.01068">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Augmenting and Tuning Knowledge Graph Embeddings </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Bamler,+R">Robert Bamler</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Salehi,+F">Farnood Salehi</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mandt,+S">Stephan Mandt</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Published version, Conference on Uncertainty in Artificial Intelligence (UAI 2019) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Artificial Intelligence (cs.AI); Machine Learning (cs.LG) </div> </div> </dd> <dt> <a name='item36'>[36]</a> <a href ="/abs/1907.01110" title="Abstract" id="1907.01110"> arXiv:1907.01110 </a> [<a href="/pdf/1907.01110" title="Download PDF" id="pdf-1907.01110" aria-labelledby="pdf-1907.01110">pdf</a>, <a href="/format/1907.01110" title="Other formats" id="oth-1907.01110" aria-labelledby="oth-1907.01110">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Robust analogs to the Coefficient of Variation </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Arachchige,+C+N+P+G">Chandima N. P. G. Arachchige</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Prendergast,+L+A">Luke A. Prendergast</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Staudte,+R+G">Robert G. Staudte</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 30 pages, 2 figures Changed "analogues" to "analogs" in title to match published version. Journal of Applied Statistics (2020) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span> </div> </div> </dd> <dt> <a name='item37'>[37]</a> <a href ="/abs/1907.01136" title="Abstract" id="1907.01136"> arXiv:1907.01136 </a> [<a href="/pdf/1907.01136" title="Download PDF" id="pdf-1907.01136" aria-labelledby="pdf-1907.01136">pdf</a>, <a href="https://arxiv.org/html/1907.01136v6" title="View HTML" id="html-1907.01136" aria-labelledby="html-1907.01136" rel="noopener noreferrer" target="_blank">html</a>, <a href="/format/1907.01136" title="Other formats" id="oth-1907.01136" aria-labelledby="oth-1907.01136">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Finding Outliers in Gaussian Model-Based Clustering </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Clark,+K+M">Katharine M. Clark</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=McNicholas,+P+D">Paul D. McNicholas</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item38'>[38]</a> <a href ="/abs/1907.01145" title="Abstract" id="1907.01145"> arXiv:1907.01145 </a> [<a href="/pdf/1907.01145" title="Download PDF" id="pdf-1907.01145" aria-labelledby="pdf-1907.01145">pdf</a>, <a href="/format/1907.01145" title="Other formats" id="oth-1907.01145" aria-labelledby="oth-1907.01145">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> The generalized orthogonal Procrustes problem in the high noise regime </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Pumir,+T">Thomas Pumir</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Singer,+A">Amit Singer</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Boumal,+N">Nicolas Boumal</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Information and Inference: A Journal of the IMA, iaaa035, 2021 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span> </div> </div> </dd> <dt> <a name='item39'>[39]</a> <a href ="/abs/1907.01170" title="Abstract" id="1907.01170"> arXiv:1907.01170 </a> [<a href="/pdf/1907.01170" title="Download PDF" id="pdf-1907.01170" aria-labelledby="pdf-1907.01170">pdf</a>, <a href="/format/1907.01170" title="Other formats" id="oth-1907.01170" aria-labelledby="oth-1907.01170">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayesian Analysis of High-dimensional Discrete Graphical Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Bhattacharyya,+A">Anwesha Bhattacharyya</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Atchade,+Y">Yves Atchade</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Computation (stat.CO) </div> </div> </dd> <dt> <a name='item40'>[40]</a> <a href ="/abs/1907.01175" title="Abstract" id="1907.01175"> arXiv:1907.01175 </a> [<a href="/pdf/1907.01175" title="Download PDF" id="pdf-1907.01175" aria-labelledby="pdf-1907.01175">pdf</a>, <a href="/format/1907.01175" title="Other formats" id="oth-1907.01175" aria-labelledby="oth-1907.01175">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Volatility Analysis with Realized GARCH-Ito Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Song,+X">Xinyu Song</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kim,+D">Donggyu Kim</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yuan,+H">Huiling Yuan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cui,+X">Xiangyu Cui</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lu,+Z">Zhiping Lu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhou,+Y">Yong Zhou</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+Y">Yazhen Wang</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 39 pages, 4 tables, 3 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Applications (stat.AP) </div> </div> </dd> <dt> <a name='item41'>[41]</a> <a href ="/abs/1907.01181" title="Abstract" id="1907.01181"> arXiv:1907.01181 </a> [<a href="/pdf/1907.01181" title="Download PDF" id="pdf-1907.01181" aria-labelledby="pdf-1907.01181">pdf</a>, <a href="/format/1907.01181" title="Other formats" id="oth-1907.01181" aria-labelledby="oth-1907.01181">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Adaptive Partitioning Design and Analysis for Emulation of a Complex Computer Code </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Surjanovic,+S">Sonja Surjanovic</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Welch,+W+J">William J. Welch</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item42'>[42]</a> <a href ="/abs/1907.01196" title="Abstract" id="1907.01196"> arXiv:1907.01196 </a> [<a href="/pdf/1907.01196" title="Download PDF" id="pdf-1907.01196" aria-labelledby="pdf-1907.01196">pdf</a>, <a href="/format/1907.01196" title="Other formats" id="oth-1907.01196" aria-labelledby="oth-1907.01196">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Large Volatility Matrix Prediction with High-Frequency Data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Song,+X">Xinyu Song</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Research method similar to the one covered in the manuscript has been examined already </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Econometrics (econ.EM) </div> </div> </dd> <dt> <a name='item43'>[43]</a> <a href ="/abs/1907.01223" title="Abstract" id="1907.01223"> arXiv:1907.01223 </a> [<a href="/pdf/1907.01223" title="Download PDF" id="pdf-1907.01223" aria-labelledby="pdf-1907.01223">pdf</a>, <a href="/format/1907.01223" title="Other formats" id="oth-1907.01223" aria-labelledby="oth-1907.01223">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Specification testing in semi-parametric transformation models </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Kloodt,+N">Nick Kloodt</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Neumeyer,+N">Natalie Neumeyer</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Van+Keilegom,+I">Ingrid Van Keilegom</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 54 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span> </div> </div> </dd> <dt> <a name='item44'>[44]</a> <a href ="/abs/1907.01248" title="Abstract" id="1907.01248"> arXiv:1907.01248 </a> [<a href="/pdf/1907.01248" title="Download PDF" id="pdf-1907.01248" aria-labelledby="pdf-1907.01248">pdf</a>, <a href="/format/1907.01248" title="Other formats" id="oth-1907.01248" aria-labelledby="oth-1907.01248">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Integrated Nested Laplace Approximations (INLA) </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Martino,+S">Sara Martino</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Riebler,+A">Andrea Riebler</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span> </div> </div> </dd> <dt> <a name='item45'>[45]</a> <a href ="/abs/1907.01306" title="Abstract" id="1907.01306"> arXiv:1907.01306 </a> [<a href="/pdf/1907.01306" title="Download PDF" id="pdf-1907.01306" aria-labelledby="pdf-1907.01306">pdf</a>, <a href="/format/1907.01306" title="Other formats" id="oth-1907.01306" aria-labelledby="oth-1907.01306">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Elicitability and Identifiability of Systemic Risk Measures </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Fissler,+T">Tobias Fissler</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Hlavinov%C3%A1,+J">Jana Hlavinov谩</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Rudloff,+B">Birgit Rudloff</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 42 pages, 3 figures + supplementary material (6 pages, 2 figures) </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Finance and Stochastics (2021), Volume 25, No. 1, 133-165 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Mathematical Finance (q-fin.MF); Risk Management (q-fin.RM); Statistical Finance (q-fin.ST) </div> </div> </dd> <dt> <a name='item46'>[46]</a> <a href ="/abs/1907.01333" title="Abstract" id="1907.01333"> arXiv:1907.01333 </a> [<a href="/pdf/1907.01333" title="Download PDF" id="pdf-1907.01333" aria-labelledby="pdf-1907.01333">pdf</a>, <a href="/format/1907.01333" title="Other formats" id="oth-1907.01333" aria-labelledby="oth-1907.01333">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On Global-local Shrinkage Priors for Count Data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Hamura,+Y">Yasuyuki Hamura</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Irie,+K">Kaoru Irie</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sugasawa,+S">Shonosuke Sugasawa</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 28 pages (main text) + 14 pages (supplementary material) </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item47'>[47]</a> <a href ="/abs/1907.01358" title="Abstract" id="1907.01358"> arXiv:1907.01358 </a> [<a href="/pdf/1907.01358" title="Download PDF" id="pdf-1907.01358" aria-labelledby="pdf-1907.01358">pdf</a>, <a href="/format/1907.01358" title="Other formats" id="oth-1907.01358" aria-labelledby="oth-1907.01358">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multiple Bayesian Filtering as Message Passing </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Vitetta,+G+M">Giorgio M. Vitetta</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Di+Viesti,+P">Pasquale Di Viesti</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Sirignano,+E">Emilio Sirignano</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Montorsi,+F">Francesco Montorsi</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span> </div> </div> </dd> <dt> <a name='item48'>[48]</a> <a href ="/abs/1907.01379" title="Abstract" id="1907.01379"> arXiv:1907.01379 </a> [<a href="/pdf/1907.01379" title="Download PDF" id="pdf-1907.01379" aria-labelledby="pdf-1907.01379">pdf</a>, <a href="/format/1907.01379" title="Other formats" id="oth-1907.01379" aria-labelledby="oth-1907.01379">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multidimensional Scaling on Metric Measure Spaces </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Adams,+H">Henry Adams</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Blumstein,+M">Mark Blumstein</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Kassab,+L">Lara Kassab</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> arXiv admin note: substantial text overlap with <a href="https://arxiv.org/abs/1904.07763" data-arxiv-id="1904.07763" class="link-https">arXiv:1904.07763</a> </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Rocky Mountain Journal of Mathematics 50 (2020), 397-413 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Spectral Theory (math.SP) </div> </div> </dd> <dt> <a name='item49'>[49]</a> <a href ="/abs/1907.01458" title="Abstract" id="1907.01458"> arXiv:1907.01458 </a> [<a href="/pdf/1907.01458" title="Download PDF" id="pdf-1907.01458" aria-labelledby="pdf-1907.01458">pdf</a>, <a href="/format/1907.01458" title="Other formats" id="oth-1907.01458" aria-labelledby="oth-1907.01458">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multiple competition-based FDR control for peptide detection </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Emery,+K">Kristen Emery</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Hasam,+S">Syamand Hasam</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Noble,+W+S">William Stafford Noble</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Keich,+U">Uri Keich</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Numerous changes from the initial submission including an expanded section on peptide detection (context/motivation and results), refocused and streamlined methods development section, revised and more selective figures reflecting the most recent analysis </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Applications (stat.AP) </div> </div> </dd> <dt> <a name='item50'>[50]</a> <a href ="/abs/1907.01505" title="Abstract" id="1907.01505"> arXiv:1907.01505 </a> [<a href="/pdf/1907.01505" title="Download PDF" id="pdf-1907.01505" aria-labelledby="pdf-1907.01505">pdf</a>, <a href="/format/1907.01505" title="Other formats" id="oth-1907.01505" aria-labelledby="oth-1907.01505">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Adaptive Approximate Bayesian Computation Tolerance Selection </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Simola,+U">Umberto Simola</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Cisewski-Kehe,+J">Jessica Cisewski-Kehe</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Gutmann,+M+U">Michael U. Gutmann</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Corander,+J">Jukka Corander</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 26 pages, 8 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span>; Applications (stat.AP); Methodology (stat.ME) </div> </div> </dd> </dl> <div class='paging'>Total of 1336 entries : <span>1-50</span> <a href=/list/stat/2019-07?skip=50&show=50>51-100</a> <a href=/list/stat/2019-07?skip=100&show=50>101-150</a> <a href=/list/stat/2019-07?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/stat/2019-07?skip=1300&show=50>1301-1336</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/stat/2019-07?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat/2019-07?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat/2019-07?skip=0&show=2000 rel="nofollow"> all</a> </div> </div> </div> </div> </main> <footer style="clear: both;"> <div class="columns is-desktop" role="navigation" aria-label="Secondary" style="margin: -0.75em -0.75em 0.75em -0.75em"> <!-- Macro-Column 1 --> <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; 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