-
作者：Bodelet, Julien; Blanc, Guillaume; Shan, Jiajun; Muniz Terrera, Graciela; Chen, Oliver Y.
作者单位：University of Lausanne; Centre Hospitalier Universitaire Vaudois (CHUV); University of Lausanne; University of Zurich; University of Geneva; University System of Ohio; Ohio University; University of Edinburgh
摘要：Large and complex datasets, emerging from technological advancements in fields such as genomics and brain imaging, hold ample promise for gaining new scientific insights. Yet, their inherent nonlinearity and high dimensionality present considerable theoretical, methodological, and application challenges to the statistics and machine learning community. This article introduces Statistical Quantile Learning (SQL), a new nonparametric method for estimating large additive latent variable models. T...
-
作者：Gao, Youqian; Dai, Ben
作者单位：Chinese University of Hong Kong
摘要：The technique of word embedding is widely used in natural language processing (NLP) to represent words as numerical vectors in textual datasets. However, the estimation of word embedding may suffer from severe overfitting due to the huge variety of words. To address the issue, this article proposes a novel regularization framework that recognizes and accounts for the word-level distribution discrepancy-a common phenomenon in a range of NLP tasks where word distributions are noticeably disparat...
-
作者：Morey, Richard D.; Davis-Stober, Clintin P.
作者单位：Cardiff University; University of Missouri System; University of Missouri Columbia; University of Missouri System; University of Missouri Columbia
摘要：The P-curve is a widely used suite of meta-analytic tests advertised for detecting problems in sets of studies. They are based on nonparametric combinations of p values (e.g., Marden) across significant (p < .05) studies and are variously claimed to detect evidential value, lack of evidential value, and left skew in p values. We show that these tests do not have the properties ascribed to them. Moreover, they fail basic desiderata for tests, including admissibility and monotonicity. In light o...
-
作者：Watson, Samuel I.; Smith, Thomas A.
作者单位：University of Birmingham
摘要：In this article, we consider randomized trial design to evaluate interventions with spatially or spatio-temporally heterogeneous effects. A common approach in this setting is the cluster randomized trial. In many cases, clusters are constituted as discrete subdivisions of a contiguous area of interest. However, cluster trials designed in this way may suffer from issues of spillover and may fail to capture the relevant spatial and temporal effects. We define possible randomization schemes and c...
-
作者：He, Yi; Einmahl, John H. J.
作者单位：Eastern Institute of Technology, Ningbo; Tilburg University
摘要：In the general setting of independent data with possibly very different distributions, extreme value estimators inevitably target the tail of the average distribution function. We consider all possible cases, that is, the extreme value index of the average distribution can be negative, zero, or positive, and we present novel asymptotic theory for the moment estimator. Our results require a different and much more challenging proof than those for the power-law case and are based on a uniform ce...
-
作者：Yao, Yisha; Hu, Yue; Wang, Shiying; Dai, Wei; Liu, Zihuan; Zhang, Heping
作者单位：Columbia University; Yale University; Yale University
摘要：The organization of human brain subnetworks is fundamental to understanding cognition and neuropsychiatric health. Existing approaches predominantly construct subnetworks by clustering brain regions according to measured imaging phenotypes or functional correlation. Although successful, such phenotype-based parcellations reflect composite effects of genetics, environment, lifestyle, and measurement noise, thereby limiting biological interpretability and obscuring subnetworks attributable to sp...
-
作者：Doss, Charles R.
作者单位：University of Minnesota System; University of Minnesota Twin Cities
摘要：We study nonparametric inference for the causal dose-response curve when the treatment variable is continuous rather than discrete. We develop doubly robust confidence intervals for the continuous treatment effect curve (at a fixed point) under the assumption that it is monotonic, based on inverting a likelihood ratio-type test. Monotonicity of the treatment effect curve is often a very natural assumption, and this assumption removes the need to choose a smoothing or tuning parameter for the n...
-
作者：Koner, Salil
-
作者：Ni, Yang
作者单位：University of Texas System; University of Texas Austin
-
作者：Betancourt, Brenda
作者单位：George Mason University
