Statistics Nov 2013

<!DOCTYPE html> <html lang="en"> <head> <title>Statistics Nov 2013</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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href=/list/stat/2013-11?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat/2013-11?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat/2013-11?skip=0&show=2000 rel="nofollow"> all</a> </div> <dl id='articles'> <dt> <a name='item1'>[1]</a> <a href ="/abs/1311.0072" title="Abstract" id="1311.0072"> arXiv:1311.0072 </a> [<a href="/pdf/1311.0072" title="Download PDF" id="pdf-1311.0072" aria-labelledby="pdf-1311.0072">pdf</a>, <a href="/format/1311.0072" title="Other formats" id="oth-1311.0072" aria-labelledby="oth-1311.0072">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayesian inference as iterated random functions with applications to sequential inference in graphical models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Amini,+A+A">Arash A. Amini</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Nguyen,+X">XuanLong Nguyen</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Statistics Theory (math.ST); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item2'>[2]</a> <a href ="/abs/1311.0081" title="Abstract" id="1311.0081"> arXiv:1311.0081 </a> [<a href="/pdf/1311.0081" title="Download PDF" id="pdf-1311.0081" aria-labelledby="pdf-1311.0081">pdf</a>, <a href="/format/1311.0081" title="Other formats" id="oth-1311.0081" aria-labelledby="oth-1311.0081">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> To P or not to P: on the evidential nature of P-values and their place in scientific inference </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Lew,+M+J">Michael J. Lew</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 31 pages, 9 figures and R code </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item3'>[3]</a> <a href ="/abs/1311.0085" title="Abstract" id="1311.0085"> arXiv:1311.0085 </a> [<a href="/pdf/1311.0085" title="Download PDF" id="pdf-1311.0085" aria-labelledby="pdf-1311.0085">pdf</a>, <a href="/format/1311.0085" title="Other formats" id="oth-1311.0085" aria-labelledby="oth-1311.0085">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Selection and Estimation for Mixed Graphical Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Chen,+S">Shizhe Chen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Witten,+D">Daniela Witten</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Shojaie,+A">Ali Shojaie</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='item4'>[4]</a> <a href ="/abs/1311.0096" title="Abstract" id="1311.0096"> arXiv:1311.0096 </a> [<a href="/pdf/1311.0096" title="Download PDF" id="pdf-1311.0096" aria-labelledby="pdf-1311.0096">pdf</a>, <a href="/format/1311.0096" title="Other formats" id="oth-1311.0096" aria-labelledby="oth-1311.0096">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Higher-Order Improvements of the Sieve Bootstrap for Fractionally Integrated Processes </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Poskitt,+D+S">D. S. Poskitt</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Grose,+S+D">Simone D. Grose</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Martin,+G+M">Gael M. Martin</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Published in Journal of Econometrics, 2015. Volume 188, 94-100 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item5'>[5]</a> <a href ="/abs/1311.0098" title="Abstract" id="1311.0098"> arXiv:1311.0098 </a> [<a href="/pdf/1311.0098" title="Download PDF" id="pdf-1311.0098" aria-labelledby="pdf-1311.0098">pdf</a>, <a href="/format/1311.0098" title="Other formats" id="oth-1311.0098" aria-labelledby="oth-1311.0098">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Bayesian framework for functional time series analysis </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Petris,+G">Giovanni Petris</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='item6'>[6]</a> <a href ="/abs/1311.0219" title="Abstract" id="1311.0219"> arXiv:1311.0219 </a> [<a href="/pdf/1311.0219" title="Download PDF" id="pdf-1311.0219" aria-labelledby="pdf-1311.0219">pdf</a>, <a href="/format/1311.0219" title="Other formats" id="oth-1311.0219" aria-labelledby="oth-1311.0219">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Joint Estimation of Multiple Graphical Models from High Dimensional Time Series </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Qiu,+H">Huitong Qiu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Han,+F">Fang Han</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Liu,+H">Han Liu</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Caffo,+B">Brian Caffo</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 40 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span> </div> </div> </dd> <dt> <a name='item7'>[7]</a> <a href ="/abs/1311.0270" title="Abstract" id="1311.0270"> arXiv:1311.0270 </a> [<a href="/pdf/1311.0270" title="Download PDF" id="pdf-1311.0270" aria-labelledby="pdf-1311.0270">pdf</a>, <a href="/format/1311.0270" title="Other formats" id="oth-1311.0270" aria-labelledby="oth-1311.0270">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> There is a VaR beyond usual approximations </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Kratz,+M">Marie Kratz</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 33 pages, 5 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Risk Management (q-fin.RM) </div> </div> </dd> <dt> <a name='item8'>[8]</a> <a href ="/abs/1311.0274" title="Abstract" id="1311.0274"> arXiv:1311.0274 </a> [<a href="/pdf/1311.0274" title="Download PDF" id="pdf-1311.0274" aria-labelledby="pdf-1311.0274">pdf</a>, <a href="/format/1311.0274" title="Other formats" id="oth-1311.0274" aria-labelledby="oth-1311.0274">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Nearly Optimal Sample Size in Hypothesis Testing for High-Dimensional Regression </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Javanmard,+A">Adel Javanmard</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Montanari,+A">Andrea Montanari</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 21 pages, short version appears in Annual Allerton Conference on Communication, Control and Computing, 2013 </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 (cs.LG); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item9'>[9]</a> <a href ="/abs/1311.0291" title="Abstract" id="1311.0291"> arXiv:1311.0291 </a> [<a href="/pdf/1311.0291" title="Download PDF" id="pdf-1311.0291" aria-labelledby="pdf-1311.0291">pdf</a>, <a href="/format/1311.0291" title="Other formats" id="oth-1311.0291" aria-labelledby="oth-1311.0291">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Improved Precision in Estimating Average Treatment Effects </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Pitkin,+E">Emil Pitkin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Berk,+R">Richard Berk</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Brown,+L">Lawrence Brown</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Buja,+A">Andreas Buja</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=George,+E">Ed George</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhang,+K">Kai Zhang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Zhao,+L">Linda Zhao</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 22 pages, 1 figure </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item10'>[10]</a> <a href ="/abs/1311.0307" title="Abstract" id="1311.0307"> arXiv:1311.0307 </a> [<a href="/pdf/1311.0307" title="Download PDF" id="pdf-1311.0307" aria-labelledby="pdf-1311.0307">pdf</a>, <a href="/format/1311.0307" title="Other formats" id="oth-1311.0307" aria-labelledby="oth-1311.0307">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Shared kernel Bayesian screening </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Lock,+E+F">Eric F. Lock</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dunson,+D+B">David B. Dunson</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Author version of article published in Biometrika; 23 pages, 9 figures </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Biometrika 102(4), 829-842, 2015 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item11'>[11]</a> <a href ="/abs/1311.0317" title="Abstract" id="1311.0317"> arXiv:1311.0317 </a> [<a href="/pdf/1311.0317" title="Download PDF" id="pdf-1311.0317" aria-labelledby="pdf-1311.0317">pdf</a>, <a href="/format/1311.0317" title="Other formats" id="oth-1311.0317" aria-labelledby="oth-1311.0317">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Parsimonious Shifted Asymmetric Laplace Mixtures </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Franczak,+B+C">Brian C. Franczak</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=McNicholas,+P+D">Paul D. McNicholas</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Browne,+R+P">Ryan P. Browne</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Murray,+P+M">Paula M. Murray</a></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='item12'>[12]</a> <a href ="/abs/1311.0360" title="Abstract" id="1311.0360"> arXiv:1311.0360 </a> [<a href="/pdf/1311.0360" title="Download PDF" id="pdf-1311.0360" aria-labelledby="pdf-1311.0360">pdf</a>, <a href="/format/1311.0360" title="Other formats" id="oth-1311.0360" aria-labelledby="oth-1311.0360">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Multivariate Generalized Gaussian Process Models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Chan,+A+B">Antoni B. Chan</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span> </div> </div> </dd> <dt> <a name='item13'>[13]</a> <a href ="/abs/1311.0407" title="Abstract" id="1311.0407"> arXiv:1311.0407 </a> [<a href="/pdf/1311.0407" title="Download PDF" id="pdf-1311.0407" aria-labelledby="pdf-1311.0407">pdf</a>, <a href="/format/1311.0407" title="Other formats" id="oth-1311.0407" aria-labelledby="oth-1311.0407">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Audio Texture Synthesis with Scattering Moments </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Bruna,+J">Joan Bruna</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mallat,+S">St茅phane Mallat</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 5 pages, 2 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Sound (cs.SD) </div> </div> </dd> <dt> <a name='item14'>[14]</a> <a href ="/abs/1311.0412" title="Abstract" id="1311.0412"> arXiv:1311.0412 </a> [<a href="/pdf/1311.0412" title="Download PDF" id="pdf-1311.0412" aria-labelledby="pdf-1311.0412">pdf</a>, <a href="/format/1311.0412" title="Other formats" id="oth-1311.0412" aria-labelledby="oth-1311.0412">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimal Uniform Convergence Rates for Sieve Nonparametric Instrumental Variables Regression </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Chen,+X">Xiaohong Chen</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Christensen,+T">Timothy Christensen</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Statistics Theory (math.ST)</span>; Econometrics (econ.EM); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item15'>[15]</a> <a href ="/abs/1311.0416" title="Abstract" id="1311.0416"> arXiv:1311.0416 </a> [<a href="/pdf/1311.0416" title="Download PDF" id="pdf-1311.0416" aria-labelledby="pdf-1311.0416">pdf</a>, <a href="/format/1311.0416" title="Other formats" id="oth-1311.0416" aria-labelledby="oth-1311.0416">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Structured functional regression models for high-dimensional spatial spectroscopy data </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Amini,+A+A">Arash A. Amini</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Levina,+E">Elizaveta Levina</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Shedden,+K+A">Kerby A. Shedden</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='item16'>[16]</a> <a href ="/abs/1311.0431" title="Abstract" id="1311.0431"> arXiv:1311.0431 </a> [<a href="/pdf/1311.0431" title="Download PDF" id="pdf-1311.0431" aria-labelledby="pdf-1311.0431">pdf</a>, <a href="/format/1311.0431" title="Other formats" id="oth-1311.0431" aria-labelledby="oth-1311.0431">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Gene-Proximity Models For Genome-Wide Association Studies </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Johnston,+I">Ian Johnston</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Hancock,+T">Timothy Hancock</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mamitsuka,+H">Hiroshi Mamitsuka</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Carvalho,+L">Luis Carvalho</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 27 pages, 9 figures, 2 tables </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span> </div> </div> </dd> <dt> <a name='item17'>[17]</a> <a href ="/abs/1311.0463" title="Abstract" id="1311.0463"> arXiv:1311.0463 </a> [<a href="/pdf/1311.0463" title="Download PDF" id="pdf-1311.0463" aria-labelledby="pdf-1311.0463">pdf</a>, <a href="/format/1311.0463" title="Other formats" id="oth-1311.0463" aria-labelledby="oth-1311.0463">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Functional Factorial K-means Analysis </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Yamamoto,+M">Michio Yamamoto</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Terada,+Y">Yoshikazu Terada</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 39 pages, 17 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='item18'>[18]</a> <a href ="/abs/1311.0466" title="Abstract" id="1311.0466"> arXiv:1311.0466 </a> [<a href="/pdf/1311.0466" title="Download PDF" id="pdf-1311.0466" aria-labelledby="pdf-1311.0466">pdf</a>, <a href="/format/1311.0466" title="Other formats" id="oth-1311.0466" aria-labelledby="oth-1311.0466">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Thompson Sampling for Complex Bandit Problems </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Gopalan,+A">Aditya Gopalan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mannor,+S">Shie Mannor</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Mansour,+Y">Yishay Mansour</a></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='item19'>[19]</a> <a href ="/abs/1311.0468" title="Abstract" id="1311.0468"> arXiv:1311.0468 </a> [<a href="/pdf/1311.0468" title="Download PDF" id="pdf-1311.0468" aria-labelledby="pdf-1311.0468">pdf</a>, <a href="/format/1311.0468" title="Other formats" id="oth-1311.0468" aria-labelledby="oth-1311.0468">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Thompson Sampling for Online Learning with Linear Experts </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Gopalan,+A">Aditya Gopalan</a></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='item20'>[20]</a> <a href ="/abs/1311.0510" title="Abstract" id="1311.0510"> arXiv:1311.0510 </a> [<a href="/pdf/1311.0510" title="Download PDF" id="pdf-1311.0510" aria-labelledby="pdf-1311.0510">pdf</a>, <a href="/format/1311.0510" title="Other formats" id="oth-1311.0510" aria-labelledby="oth-1311.0510">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Compressed matched filter for non-Gaussian noise </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Vovnoboy,+J">Jakob Vovnoboy</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wiesel,+A">Ami Wiesel</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='item21'>[21]</a> <a href ="/abs/1311.0524" title="Abstract" id="1311.0524"> arXiv:1311.0524 </a> [<a href="/pdf/1311.0524" title="Download PDF" id="pdf-1311.0524" aria-labelledby="pdf-1311.0524">pdf</a>, <a href="/format/1311.0524" title="Other formats" id="oth-1311.0524" aria-labelledby="oth-1311.0524">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> A Bayesian Residual-Based Test for Cointegration </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Furmston,+T">Thomas Furmston</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Hailes,+S">Stephen Hailes</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Morton,+A+J">A. Jennifer Morton</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='item22'>[22]</a> <a href ="/abs/1311.0562" title="Abstract" id="1311.0562"> arXiv:1311.0562 </a> [<a href="/pdf/1311.0562" title="Download PDF" id="pdf-1311.0562" aria-labelledby="pdf-1311.0562">pdf</a>, <a href="/format/1311.0562" title="Other formats" id="oth-1311.0562" aria-labelledby="oth-1311.0562">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> LP Mixed Data Science : Outline of Theory </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Parzen,+E">Emanuel Parzen</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Mukhopadhyay,+S">Subhadeep Mukhopadhyay</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='item23'>[23]</a> <a href ="/abs/1311.0587" title="Abstract" id="1311.0587"> arXiv:1311.0587 </a> [<a href="/pdf/1311.0587" title="Download PDF" id="pdf-1311.0587" aria-labelledby="pdf-1311.0587">pdf</a>, <a href="/format/1311.0587" title="Other formats" id="oth-1311.0587" aria-labelledby="oth-1311.0587">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> High-dimensional $p$-norms </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Biau,+G">G茅rard Biau</a> (LSTA, LPMA, DMA, INRIA Paris - Rocquencourt), <a href="https://arxiv.org/search/math?searchtype=author&query=Mason,+D+D">David D.M. Mason</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 19 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='item24'>[24]</a> <a href ="/abs/1311.0594" title="Abstract" id="1311.0594"> arXiv:1311.0594 </a> [<a href="/pdf/1311.0594" title="Download PDF" id="pdf-1311.0594" aria-labelledby="pdf-1311.0594">pdf</a>, <a href="/format/1311.0594" title="Other formats" id="oth-1311.0594" aria-labelledby="oth-1311.0594">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Covariance Estimation in Elliptical Models with Convex Structure </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Soloveychik,+I">Ilya Soloveychik</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Wiesel,+A">Ami Wiesel</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='item25'>[25]</a> <a href ="/abs/1311.0622" title="Abstract" id="1311.0622"> arXiv:1311.0622 </a> [<a href="/pdf/1311.0622" title="Download PDF" id="pdf-1311.0622" aria-labelledby="pdf-1311.0622">pdf</a>, <a href="/format/1311.0622" title="Other formats" id="oth-1311.0622" aria-labelledby="oth-1311.0622">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Stochastic Dual Coordinate Ascent with Alternating Direction Multiplier Method </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Suzuki,+T">Taiji Suzuki</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 26pages, 12 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span> </div> </div> </dd> <dt> <a name='item26'>[26]</a> <a href ="/abs/1311.0634" title="Abstract" id="1311.0634"> arXiv:1311.0634 </a> [<a href="/pdf/1311.0634" title="Download PDF" id="pdf-1311.0634" aria-labelledby="pdf-1311.0634">pdf</a>, <a href="/format/1311.0634" title="Other formats" id="oth-1311.0634" aria-labelledby="oth-1311.0634">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Real-time covariance estimation for the local level model </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Triantafyllopoulos,+K">K. Triantafyllopoulos</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 34 pages, 3 figures, 1 table </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Journal of Time Series Analysis, 2011, 32, 93-107 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item27'>[27]</a> <a href ="/abs/1311.0644" title="Abstract" id="1311.0644"> arXiv:1311.0644 </a> [<a href="/pdf/1311.0644" title="Download PDF" id="pdf-1311.0644" aria-labelledby="pdf-1311.0644">pdf</a>, <a href="/format/1311.0644" title="Other formats" id="oth-1311.0644" aria-labelledby="oth-1311.0644">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Forecasting multivariate longitudinal binary data with marginal and marginally specified models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Asar,+O">Ozgur Asar</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ilk,+O">Ozlem Ilk</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='item28'>[28]</a> <a href ="/abs/1311.0656" title="Abstract" id="1311.0656"> arXiv:1311.0656 </a> [<a href="/pdf/1311.0656" title="Download PDF" id="pdf-1311.0656" aria-labelledby="pdf-1311.0656">pdf</a>, <a href="/format/1311.0656" title="Other formats" id="oth-1311.0656" aria-labelledby="oth-1311.0656">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Explaining the behavior of joint and marginal Monte Carlo estimators in latent variable models with independence assumptions </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Vitoratou,+S">Silia Vitoratou</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ntzoufras,+I">Ioannis Ntzoufras</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Moustaki,+I">Irini Moustaki</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='item29'>[29]</a> <a href ="/abs/1311.0660" title="Abstract" id="1311.0660"> arXiv:1311.0660 </a> [<a href="/pdf/1311.0660" title="Download PDF" id="pdf-1311.0660" aria-labelledby="pdf-1311.0660">pdf</a>, <a href="/format/1311.0660" title="Other formats" id="oth-1311.0660" aria-labelledby="oth-1311.0660">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Identifying Clusters in Bayesian Disease Mapping </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Anderson,+C">Craig Anderson</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lee,+D">Duncan Lee</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dean,+N">Nema Dean</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='item30'>[30]</a> <a href ="/abs/1311.0662" title="Abstract" id="1311.0662"> arXiv:1311.0662 </a> [<a href="/pdf/1311.0662" title="Download PDF" id="pdf-1311.0662" aria-labelledby="pdf-1311.0662">pdf</a>, <a href="/format/1311.0662" title="Other formats" id="oth-1311.0662" aria-labelledby="oth-1311.0662">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Linear Estimating Equations for Exponential Families with Application to Gaussian Linear Concentration Models </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Forbes,+P+G+M">Peter G. M. Forbes</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Lauritzen,+S">Steffen Lauritzen</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='item31'>[31]</a> <a href ="/abs/1311.0669" title="Abstract" id="1311.0669"> arXiv:1311.0669 </a> [<a href="/pdf/1311.0669" title="Download PDF" id="pdf-1311.0669" aria-labelledby="pdf-1311.0669">pdf</a>, <a href="/format/1311.0669" title="Other formats" id="oth-1311.0669" aria-labelledby="oth-1311.0669">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> H枚lder Continuity of the Spectral Measures for One-Dimensional Schr枚dinger Operator in Exponential Regime </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Liu,+W">Wencai Liu</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Yuan,+X">Xiaoping Yuan</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> J. Math. Phys. 56 (2015), no. 1, 012701, 21 pp </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='item32'>[32]</a> <a href ="/abs/1311.0674" title="Abstract" id="1311.0674"> arXiv:1311.0674 </a> [<a href="/pdf/1311.0674" title="Download PDF" id="pdf-1311.0674" aria-labelledby="pdf-1311.0674">pdf</a>, <a href="/format/1311.0674" title="Other formats" id="oth-1311.0674" aria-labelledby="oth-1311.0674">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On the use of marginal posteriors in marginal likelihood estimation via importance-sampling </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Perrakis,+K">K. Perrakis</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Ntzoufras,+I">I. Ntzoufras</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Tsionas,+E">E.G. Tsionas</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Computational Statistics & Data Analysis Volume 77, September 2014, Pages 54-69 </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/1311.0686" title="Abstract" id="1311.0686"> arXiv:1311.0686 </a> [<a href="/pdf/1311.0686" title="Download PDF" id="pdf-1311.0686" aria-labelledby="pdf-1311.0686">pdf</a>, <a href="/format/1311.0686" title="Other formats" id="oth-1311.0686" aria-labelledby="oth-1311.0686">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Particle Metropolis-Hastings using gradient and Hessian information </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Dahlin,+J">Johan Dahlin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lindsten,+F">Fredrik Lindsten</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Sch%C3%B6n,+T+B">Thomas B. Sch枚n</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 27 pages, 5 figures, 2 tables. The final publication is available at Springer via: <a href="http://dx.doi.org/10.1007/s11222-014-9510-0" rel="external noopener nofollow" class="link-external link-http">this http URL</a> </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Statistics and Computing, Volume 25, Issue 1, pp 81-92, 2015 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item34'>[34]</a> <a href ="/abs/1311.0689" title="Abstract" id="1311.0689"> arXiv:1311.0689 </a> [<a href="/pdf/1311.0689" title="Download PDF" id="pdf-1311.0689" aria-labelledby="pdf-1311.0689">pdf</a>, <a href="/format/1311.0689" title="Other formats" id="oth-1311.0689" aria-labelledby="oth-1311.0689">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Particle filter-based Gaussian process optimisation for parameter inference </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Dahlin,+J">Johan Dahlin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lindsten,+F">Fredrik Lindsten</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted for publication in proceedings of the 19th World Congress of the International Federation of Automatic Control (IFAC), Cape Town, South Africa, August 2014. 6 pages, 4 figures </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span>; Machine Learning (stat.ML) </div> </div> </dd> <dt> <a name='item35'>[35]</a> <a href ="/abs/1311.0701" title="Abstract" id="1311.0701"> arXiv:1311.0701 </a> [<a href="/pdf/1311.0701" title="Download PDF" id="pdf-1311.0701" aria-labelledby="pdf-1311.0701">pdf</a>, <a href="/format/1311.0701" title="Other formats" id="oth-1311.0701" aria-labelledby="oth-1311.0701">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> On Fast Dropout and its Applicability to Recurrent Networks </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Bayer,+J">Justin Bayer</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Osendorfer,+C">Christian Osendorfer</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Korhammer,+D">Daniela Korhammer</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Chen,+N">Nutan Chen</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Urban,+S">Sebastian Urban</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=van+der+Smagt,+P">Patrick van der Smagt</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> The experiments for the Penn Treebank corpus were erroneous and have been stripped from this version </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span>; Machine Learning (cs.LG); Neural and Evolutionary Computing (cs.NE) </div> </div> </dd> <dt> <a name='item36'>[36]</a> <a href ="/abs/1311.0707" title="Abstract" id="1311.0707"> arXiv:1311.0707 </a> [<a href="/pdf/1311.0707" title="Download PDF" id="pdf-1311.0707" aria-labelledby="pdf-1311.0707">pdf</a>, <a href="/format/1311.0707" title="Other formats" id="oth-1311.0707" aria-labelledby="oth-1311.0707">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Generative Modelling for Unsupervised Score Calibration </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Br%C3%BCmmer,+N">Niko Br眉mmer</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Garcia-Romero,+D">Daniel Garcia-Romero</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Accepted for ICASSP 2014 </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='item37'>[37]</a> <a href ="/abs/1311.0737" title="Abstract" id="1311.0737"> arXiv:1311.0737 </a> [<a href="/pdf/1311.0737" title="Download PDF" id="pdf-1311.0737" aria-labelledby="pdf-1311.0737">pdf</a>, <a href="/format/1311.0737" title="Other formats" id="oth-1311.0737" aria-labelledby="oth-1311.0737">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Compression Limits for Random Vectors with Linearly Parameterized Second-Order Statistics </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Romero,+D">Daniel Romero</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Lopez-Valcarce,+R">Roberto Lopez-Valcarce</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Leus,+G">Geert Leus</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 15 pages, 2 figures, 1 table, submitted to IEEE Transactions on Information Theory on Nov. 4, 2013 </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='item38'>[38]</a> <a href ="/abs/1311.0811" title="Abstract" id="1311.0811"> arXiv:1311.0811 </a> [<a href="/pdf/1311.0811" title="Download PDF" id="pdf-1311.0811" aria-labelledby="pdf-1311.0811">pdf</a>, <a href="/format/1311.0811" title="Other formats" id="oth-1311.0811" aria-labelledby="oth-1311.0811">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Oracle Inequalities for High Dimensional Vector Autoregressions </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Kock,+A+B">Anders Bredahl Kock</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Callot,+L+A">Laurent A.F. Callot</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 39 pages. This is a revised version of an article not previously circulated on arXiv </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='item39'>[39]</a> <a href ="/abs/1311.0834" title="Abstract" id="1311.0834"> arXiv:1311.0834 </a> [<a href="/pdf/1311.0834" title="Download PDF" id="pdf-1311.0834" aria-labelledby="pdf-1311.0834">pdf</a>, <a href="/format/1311.0834" title="Other formats" id="oth-1311.0834" aria-labelledby="oth-1311.0834">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Smooth backfitting in additive inverse regression </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Bissantz,+N">Nicolai Bissantz</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dette,+H">Holger Dette</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Hildebrandt,+T">Thimo Hildebrandt</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Keywords: inverse regression; additive models; curse of dimensionality; smooth backfitting Mathematical subject classification: Primary: 62G20; Secondary 15A29 Pages: 26 Figures: 3 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item40'>[40]</a> <a href ="/abs/1311.0835" title="Abstract" id="1311.0835"> arXiv:1311.0835 </a> [<a href="/pdf/1311.0835" title="Download PDF" id="pdf-1311.0835" aria-labelledby="pdf-1311.0835">pdf</a>, <a href="/format/1311.0835" title="Other formats" id="oth-1311.0835" aria-labelledby="oth-1311.0835">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimal designs for nonlinear regression models with respect to non-informative priors </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Burghaus,+I">Ina Burghaus</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dette,+H">Holger Dette</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Keywords: optimal design; Bayesian optimality criteria; non-informative prior; Jeffreys prior; reference prior; polynomial regression; canonical moments; heteroscedasticity Pages: 21 Figures: 3 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span> </div> </div> </dd> <dt> <a name='item41'>[41]</a> <a href ="/abs/1311.0851" title="Abstract" id="1311.0851"> arXiv:1311.0851 </a> [<a href="/pdf/1311.0851" title="Download PDF" id="pdf-1311.0851" aria-labelledby="pdf-1311.0851">pdf</a>, <a href="/format/1311.0851" title="Other formats" id="oth-1311.0851" aria-labelledby="oth-1311.0851">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Optimal Shrinkage of Eigenvalues in the Spiked Covariance Model </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Donoho,+D+L">David L. Donoho</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Gavish,+M">Matan Gavish</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Johnstone,+I+M">Iain M. Johnstone</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='item42'>[42]</a> <a href ="/abs/1311.0907" title="Abstract" id="1311.0907"> arXiv:1311.0907 </a> [<a href="/pdf/1311.0907" title="Download PDF" id="pdf-1311.0907" aria-labelledby="pdf-1311.0907">pdf</a>, <a href="/format/1311.0907" title="Other formats" id="oth-1311.0907" aria-labelledby="oth-1311.0907">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Bayesian nonparametric inference on the Stiefel manifold </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Lin,+L">Lizhen Lin</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Rao,+V">Vinayak Rao</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dunson,+D+B">David B. Dunson</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Split the original paper into two paper, with details of computation included in <a href="https://arxiv.org/abs/1406.6652" data-arxiv-id="1406.6652" class="link-https">arXiv:1406.6652</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='item43'>[43]</a> <a href ="/abs/1311.1033" title="Abstract" id="1311.1033"> arXiv:1311.1033 </a> [<a href="/pdf/1311.1033" title="Download PDF" id="pdf-1311.1033" aria-labelledby="pdf-1311.1033">pdf</a>, <a href="/format/1311.1033" title="Other formats" id="oth-1311.1033" aria-labelledby="oth-1311.1033">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Nonparametric Bayesian models of hierarchical structure in complex networks </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Schmidt,+M+N">Mikkel N. Schmidt</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Herlau,+T">Tue Herlau</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=M%C3%B8rup,+M">Morten M酶rup</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Machine Learning (stat.ML)</span> </div> </div> </dd> <dt> <a name='item44'>[44]</a> <a href ="/abs/1311.1039" title="Abstract" id="1311.1039"> arXiv:1311.1039 </a> [<a href="/pdf/1311.1039" title="Download PDF" id="pdf-1311.1039" aria-labelledby="pdf-1311.1039">pdf</a>, <a href="/format/1311.1039" title="Other formats" id="oth-1311.1039" aria-labelledby="oth-1311.1039">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Maximum penalized likelihood estimation in semiparametric capture-recapture models </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Michelot,+T">Th茅o Michelot</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Langrock,+R">Roland Langrock</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kneib,+T">Thomas Kneib</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=King,+R">Ruth King</a></div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Applications (stat.AP)</span>; Quantitative Methods (q-bio.QM); Methodology (stat.ME) </div> </div> </dd> <dt> <a name='item45'>[45]</a> <a href ="/abs/1311.1040" title="Abstract" id="1311.1040"> arXiv:1311.1040 </a> [<a href="/pdf/1311.1040" title="Download PDF" id="pdf-1311.1040" aria-labelledby="pdf-1311.1040">pdf</a>, <a href="/format/1311.1040" title="Other formats" id="oth-1311.1040" aria-labelledby="oth-1311.1040">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Combined Independent Component Analysis and Canonical Polyadic Decomposition via Joint Diagonalization </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Gong,+X">Xiao-Feng Gong</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Wang,+C">Cheng-Yuan Wang</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Hao,+Y">Ya-Na Hao</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lin,+Q">Qiu-Hua Lin</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> IEEE China Summit & International Conference on Signal and Information Processing. IEEE, 2014:804 - 808 </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='item46'>[46]</a> <a href ="/abs/1311.1067" title="Abstract" id="1311.1067"> arXiv:1311.1067 </a> [<a href="/pdf/1311.1067" title="Download PDF" id="pdf-1311.1067" aria-labelledby="pdf-1311.1067">pdf</a>, <a href="/format/1311.1067" title="Other formats" id="oth-1311.1067" aria-labelledby="oth-1311.1067">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Approximation of improper priors </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Bioche,+C">Christele Bioche</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Druilhet,+P">Pierre Druilhet</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Published at <a href="http://dx.doi.org/10.3150/15-BEJ708" rel="external noopener nofollow" class="link-external link-http">this http URL</a> in the Bernoulli (<a href="http://isi.cbs.nl/bernoulli/" rel="external noopener nofollow" class="link-external link-http">this http URL</a>) by the International Statistical Institute/Bernoulli Society (<a href="http://isi.cbs.nl/BS/bshome.htm" rel="external noopener nofollow" class="link-external link-http">this http URL</a>) </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Bernoulli 2016, Vol. 22, No. 3, 1709-1728 </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='item47'>[47]</a> <a href ="/abs/1311.1129" title="Abstract" id="1311.1129"> arXiv:1311.1129 </a> [<a href="/pdf/1311.1129" title="Download PDF" id="pdf-1311.1129" aria-labelledby="pdf-1311.1129">pdf</a>, <a href="/format/1311.1129" title="Other formats" id="oth-1311.1129" aria-labelledby="oth-1311.1129">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Discussion of "Geodesic Monte Carlo on Embedded Manifolds" </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Byrne,+S">Simon Byrne</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Girolami,+M">Mark Girolami</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Diaconis,+P">Persi Diaconis</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Seiler,+C">Christof Seiler</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Holmes,+S">Susan Holmes</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Dryden,+I+L">Ian L. Dryden</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Kent,+J+T">John T. Kent</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Pereyra,+M">Marcelo Pereyra</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Shahbaba,+B">Babak Shahbaba</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Lan,+S">Shiwei Lan</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Streets,+J">Jeffrey Streets</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Simpson,+D">Daniel Simpson</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> Discussion of <a href="https://arxiv.org/abs/1301.6064" data-arxiv-id="1301.6064" class="link-https">arXiv:1301.6064</a>. To appear in the Scandinavian Journal of Statistics. 18 pages </div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Scandinavian Journal of Statistics (2014) 41 (1), pages 1-21 </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Computation (stat.CO)</span> </div> </div> </dd> <dt> <a name='item48'>[48]</a> <a href ="/abs/1311.1131" title="Abstract" id="1311.1131"> arXiv:1311.1131 </a> [<a href="/pdf/1311.1131" title="Download PDF" id="pdf-1311.1131" aria-labelledby="pdf-1311.1131">pdf</a>, <a href="/format/1311.1131" title="Other formats" id="oth-1311.1131" aria-labelledby="oth-1311.1131">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Compatible Weighted Proper Scoring Rules </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Forbes,+P+G+M">Peter G. M. Forbes</a></div> <div class='list-journal-ref'><span class='descriptor'>Journal-ref:</span> Biometrika (2012) 99 (4): 989-994 </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='item49'>[49]</a> <a href ="/abs/1311.1138" title="Abstract" id="1311.1138"> arXiv:1311.1138 </a> [<a href="/pdf/1311.1138" title="Download PDF" id="pdf-1311.1138" aria-labelledby="pdf-1311.1138">pdf</a>, <a href="/format/1311.1138" title="Other formats" id="oth-1311.1138" aria-labelledby="oth-1311.1138">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Analysis of the Gibbs sampler for hierarchical inverse problems </div> <div class='list-authors'><a href="https://arxiv.org/search/math?searchtype=author&query=Agapiou,+S">Sergios Agapiou</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Bardsley,+J+M">Johnathan M. Bardsley</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Papaspiliopoulos,+O">Omiros Papaspiliopoulos</a>, <a href="https://arxiv.org/search/math?searchtype=author&query=Stuart,+A+M">Andrew M. Stuart</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> to appear, SIAM/ASA Journal on Uncertainty Quantification </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='item50'>[50]</a> <a href ="/abs/1311.1189" title="Abstract" id="1311.1189"> arXiv:1311.1189 </a> [<a href="/pdf/1311.1189" title="Download PDF" id="pdf-1311.1189" aria-labelledby="pdf-1311.1189">pdf</a>, <a href="/format/1311.1189" title="Other formats" id="oth-1311.1189" aria-labelledby="oth-1311.1189">other</a>] </dt> <dd> <div class='meta'> <div class='list-title mathjax'><span class='descriptor'>Title:</span> Statistical Inference in Hidden Markov Models using $k$-segment Constraints </div> <div class='list-authors'><a href="https://arxiv.org/search/stat?searchtype=author&query=Titsias,+M+K">Michalis K. Titsias</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Yau,+C">Christopher Yau</a>, <a href="https://arxiv.org/search/stat?searchtype=author&query=Holmes,+C+C">Christopher C. Holmes</a></div> <div class='list-comments mathjax'><span class='descriptor'>Comments:</span> 37 pages </div> <div class='list-subjects'><span class='descriptor'>Subjects:</span> <span class="primary-subject">Methodology (stat.ME)</span>; Machine Learning (cs.LG); Machine Learning (stat.ML) </div> </div> </dd> </dl> <div class='paging'>Total of 307 entries : <span>1-50</span> <a href=/list/stat/2013-11?skip=50&show=50>51-100</a> <a href=/list/stat/2013-11?skip=100&show=50>101-150</a> <a href=/list/stat/2013-11?skip=150&show=50>151-200</a> <span>...</span> <a href=/list/stat/2013-11?skip=300&show=50>301-307</a> </div> <div class='morefewer'>Showing up to 50 entries per page: <a href=/list/stat/2013-11?skip=0&show=25 rel="nofollow"> fewer</a> | <a href=/list/stat/2013-11?skip=0&show=100 rel="nofollow"> more</a> | <a href=/list/stat/2013-11?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">  <div class="column" style="padding: 0;"> <div class="columns"> <div class="column"> <ul style="list-style: none; 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