-
作者：Chang, Jinyuan; Du, Yue; He, Jing; Yao, Qiwei
作者单位：Southwestern University of Finance & Economics - China; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Peking University; Southwestern University of Finance & Economics - China; University of London; London School Economics & Political Science
摘要：We propose new statistical tests, in high-dimensional settings, for testing the independence of two random vectors and their conditional independence given a third random vector. The key idea is simple, that is, we first transform each component variable to the standard normal via its marginal empirical distribution, and we then test for independence and conditional independence of the transformed random vectors using appropriate L infinity-type test statistics. While we are testing some neces...
-
作者：Rava, Bradley; Sun, Wenguang; James, Gareth M.; Tong, Xin
作者单位：University of Sydney; Zhejiang University; Zhejiang University; Emory University; University of Hong Kong
摘要：We investigate the fairness issue in classification, where automated decisions are made for individuals from different protected groups. In high-consequence scenarios, decision errors can disproportionately affect certain protected groups, leading to unfair outcomes. To address this issue, we propose a fairness-adjusted selective inference (FASI) framework and develop data-driven algorithms that achieve statistical parity by controlling the false selection rate (FSR) among protected groups. Ou...
-
作者：Boswijk, H. Peter; Laeven, Roger J. A.; Lalu, Andrei; Vladimirov, Evgenii
作者单位：University of Amsterdam; Tinbergen Institute; Tilburg University; Eindhoven University of Technology
摘要：We analyze the contagious propagation of jumps among international stock market indices, using a rich panel of high-frequency stock and options data (692,892 option contracts) over the period 2006-2015. We propose a bivariate option pricing model designed to allow for time and space amplification of jumps in option markets. We develop a semi-parametric estimation procedure, which employs a continuum of moment conditions in GMM with implied states and non-parametric high-frequency spot volatili...
-
作者：Hung, Noah Yi-Ting; Lin, Li-Hsiang; Calhoun, Vince D.
作者单位：University System of Georgia; Georgia State University; University System of Georgia; Emory University; Georgia Institute of Technology; Georgia State University
摘要：Deep neural networks (DNNs) have been widely applied to solve real-world regression problems. However, selecting optimal network structures remains a significant challenge. This study addresses this issue by linking neuron selection in DNNs to knot placement in basis expansion techniques. We introduce a difference penalty that automates knot selection, thereby simplifying the complexities of neuron selection. We name this method Deep P-Spline (DPS). This approach extends the class of models co...
-
作者：Wang, Weichen; Shi, Chengchun
作者单位：University of Hong Kong; University of London; London School Economics & Political Science
-
作者：Li, Yujue; Xue, Fei; Li, Bingxuan; Yang, Yilin; Fan, Zirui; Shu, Juan; Yang, Xiaochen; Wang, Xiyao; Lin, Jinjie; Copana, Carlos; Zhao, Bingxin
作者单位：Purdue University System; Purdue University; Purdue University System; Purdue University; University of Pennsylvania; Yale University
摘要：As large-scale biobanks provide increasing access to deep phenotyping and genomic data, genome-wide association studies (GWAS) are rapidly uncovering the genetic architecture behind various complex traits and diseases. GWAS publications typically make their summary-level data (GWAS summary statistics) publicly available, enabling further exploration of genetic overlaps between phenotypes gathered from different studies and cohorts. However, systematically analyzing high-dimensional GWAS summar...
-
作者：Kock, Anders Bredahl; Preinerstorfer, David
作者单位：University of Oxford; Vienna University of Economics & Business
摘要：Tests based on the 2- and infinity-norm have received considerable attention in high-dimensional testing problems, as they are powerful against dense and sparse alternatives, respectively. The power enhancement principle of Fan, Liao, and Yao combines these two norms to construct improved tests that are powerful against both types of alternatives. In the context of testing whether a candidate parameter satisfies a large number of moment equalities, we construct tests that harness the strength ...
-
作者：Reinbott, Felix; Janssen, Anja
作者单位：Otto von Guericke University
摘要：Principal component analysis (PCA) is one of the most popular dimension reduction techniques in statistics and is especially powerful when a multivariate distribution is concentrated near a lower-dimensional subspace. Multivariate extreme value distributions have turned out to provide challenges for the application of PCA since their constraint support impedes the detection of lower-dimensional structures and heavy-tails can imply that second moments do not exist, thereby preventing the applic...
-
作者：Dreveton, Maximilien; Kuroda, Daichi; Grossglauser, Matthias; Thiran, Patrick
作者单位：Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
摘要：Hierarchical community detection consists in finding a tree of communities where deeper levels of the hierarchy reveal finer-grained structures. There are two main classes of algorithms for this task. Divisive (top-down) algorithms recursively partition nodes into smaller communities until a stopping criterion indicates that no further splits are necessary. In contrast, agglomerative (bottom-up) algorithms first identify the smallest community structures and then repeatedly merge the communiti...
-
作者：Basak, Piyali; Maringe, Camille; Rubio, F. Javier; Linero, Antonio R.
作者单位：Merck & Company; Merck & Company USA; University of London; London School of Hygiene & Tropical Medicine; University of London; University College London; University of Texas System; University of Texas Austin
摘要：Most cancer patients are diagnosed after the age of 60, often with existing chronic health conditions (comorbidities), that can delay diagnosis and complicate treatment, prognosis, and monitoring. These comorbidities may exacerbate existing sociodemographic inequalities in cancer survival. While much research has focused on how comorbidities affect overall survival, national and international institutions typically prefer the relative survival framework for population-based studies. This frame...
