Zobrazeno 1 - 10
of 5 194
pro vyhledávání: '"Bickel, P. J."'
Autor:
Shen, Andy A., McLoughlin, Aidan, Vernon, Zoe, Lin, Jonathan, Carano, Richard A. D., Bickel, Peter J., Song, Zhuang, Huang, Haiyan
Multiple sclerosis is a chronic autoimmune disease that affects the central nervous system. Understanding multiple sclerosis progression and identifying the implicated brain structures is crucial for personalized treatment decisions. Deformation-base
Externí odkaz:
http://arxiv.org/abs/2412.09497
Autor:
Bickel, Peter J.
We follow up on Shi et al's (2020) and Cao's and my (2020) work on the local power of a new test for independence, Chatterjee (2019), and its relation to the local power properties of classical tests. We show quite generally that for testing independ
Externí odkaz:
http://arxiv.org/abs/2206.13663
Autor:
Pion-Tonachini, Luca, Bouchard, Kristofer, Martin, Hector Garcia, Peisert, Sean, Holtz, W. Bradley, Aswani, Anil, Dwivedi, Dipankar, Wainwright, Haruko, Pilania, Ghanshyam, Nachman, Benjamin, Marrone, Babetta L., Falco, Nicola, Prabhat, Arnold, Daniel, Wolf-Yadlin, Alejandro, Powers, Sarah, Climer, Sharlee, Jackson, Quinn, Carlson, Ty, Sohn, Michael, Zwart, Petrus, Kumar, Neeraj, Justice, Amy, Tomlin, Claire, Jacobson, Daniel, Micklem, Gos, Gkoutos, Georgios V., Bickel, Peter J., Cazier, Jean-Baptiste, Müller, Juliane, Webb-Robertson, Bobbie-Jo, Stevens, Rick, Anderson, Mark, Kreutz-Delgado, Ken, Mahoney, Michael W., Brown, James B.
We outline emerging opportunities and challenges to enhance the utility of AI for scientific discovery. The distinct goals of AI for industry versus the goals of AI for science create tension between identifying patterns in data versus discovering pa
Externí odkaz:
http://arxiv.org/abs/2111.13786
We develop new semiparametric methods for estimating treatment effects. We focus on settings where the outcome distributions may be thick tailed, where treatment effects may be small, where sample sizes are large and where assignment is completely ra
Externí odkaz:
http://arxiv.org/abs/2109.02603
Autor:
Ye, Yuting, Bickel, Peter J.
In this article, we study the binomial mixture model under the regime that the binomial size $m$ can be relatively large compared to the sample size $n$. This project is motivated by the GeneFishing method (Liu et al., 2019), whose output is a combin
Externí odkaz:
http://arxiv.org/abs/2107.13756
Assessing sensitivity to unmeasured confounding is an important step in observational studies, which typically estimate effects under the assumption that all confounders are measured. In this paper, we develop a sensitivity analysis framework for bal
Externí odkaz:
http://arxiv.org/abs/2102.13218
Autor:
Cao, Sky, Bickel, Peter J.
Recently, Chatterjee has introduced a new coefficient of correlation which has several natural properties. In particular, the coefficient attains its maximal value if and only if one variable is a measurable function of the other variable. In this pa
Externí odkaz:
http://arxiv.org/abs/2008.10177
A new approach to the sparse Canonical Correlation Analysis (sCCA)is proposed with the aim of discovering interpretable associations in very high-dimensional multi-view, i.e.observations of multiple sets of variables on the same subjects, problems. I
Externí odkaz:
http://arxiv.org/abs/1909.07947
Autor:
Lei, Lihua, Bickel, Peter J.
We propose the Cyclic Permutation Test (CPT) to test general linear hypotheses for linear models. This test is non-randomized and valid in finite samples with exact Type I error $\alpha$ for an arbitrary fixed design matrix and arbitrary exchangeable
Externí odkaz:
http://arxiv.org/abs/1907.06133
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