2024

最新文章

• Frederic Schoenberg and Weng Kee Wong's contribution to the Discussion of 'the Discussion Meeting on Probabilistic and statistical aspects of machine learning' AI翻译
  作者：Schoenberg, Frederic; Wong, Weng Kee
  作者单位：University of California System; University of California Los Angeles; University of California System; University of California Los Angeles
• Green's matching: an efficient approach to parameter estimation in complex dynamic systems AI翻译
  作者：Tan, Jianbin; Zhang, Guoyu; Wang, Xueqin; Huang, Hui; Yao, Fang
  作者单位：Chinese Academy of Sciences; University of Science & Technology of China, CAS; Sun Yat Sen University; Peking University; Renmin University of China
  摘要：Parameters of differential equations are essential to characterize intrinsic behaviours of dynamic systems. Numerous methods for estimating parameters in dynamic systems are computationally and/or statistically inadequate, especially for complex systems with general-order differential operators, such as motion dynamics. This article presents Green's matching, a computationally tractable and statistically efficient two-step method, which only needs to approximate trajectories in dynamic systems...
• Broadcasted nonparametric tensor regression AI翻译
  作者：Zhou, Ya; Wong, Raymond K. W.; He, Kejun
  作者单位：Renmin University of China; Texas A&M University System; Texas A&M University College Station; Renmin University of China
  摘要：We propose a novel use of a broadcasting operation, which distributes univariate functions to all entries of the tensor covariate, to model the nonlinearity in tensor regression nonparametrically. A penalized estimation and the corresponding algorithm are proposed. Our theoretical investigation, which allows the dimensions of the tensor covariate to diverge, indicates that the proposed estimation yields a desirable convergence rate. We also provide a minimax lower bound, which characterizes th...
• Adaptive bootstrap tests for composite null hypotheses in the mediation pathway analysis AI翻译
  作者：He, Yinqiu; Song, Peter X-K; Xu, Gongjun
  作者单位：University of Wisconsin System; University of Wisconsin Madison; University of Michigan System; University of Michigan; University of Michigan System; University of Michigan
  摘要：Mediation analysis aims to assess if, and how, a certain exposure influences an outcome of interest through intermediate variables. This problem has recently gained a surge of attention due to the tremendous need for such analyses in scientific fields. Testing for the mediation effect (ME) is greatly challenged by the fact that the underlying null hypothesis (i.e. the absence of MEs) is composite. Most existing mediation tests are overly conservative and thus underpowered. To overcome this sig...
• Rank-transformed subsampling: inference for multiple data splitting and exchangeable p-values AI翻译
  作者：Guo, F. Richard; Shah, Rajen D.
  作者单位：University of Michigan System; University of Michigan; University of Cambridge
  摘要：Many testing problems are readily amenable to randomized tests, such as those employing data splitting. However, despite their usefulness in principle, randomized tests have obvious drawbacks. Firstly, two analyses of the same dataset may lead to different results. Secondly, the test typically loses power because it does not fully utilize the entire sample. As a remedy to these drawbacks, we study how to combine the test statistics or p-values resulting from multiple random realizations, such ...
• Authors' reply to the Discussion of 'Parameterizing and simulating from causal models' AI翻译
  作者：Evans, Robin J.; Didelez, Vanessa
  作者单位：University of Oxford; Leibniz Association; Leibniz Institute for Prevention Research & Epidemiology (BIPS); University of Bremen; University of Bremen
• Proposers of the vote of thanks to Crane and Xu and contribution to the Discussion of 'Root and community inference on the latent growth process of a network' AI翻译
  作者：Jog, Varun; Loh, Po-Ling
  作者单位：University of Cambridge
  摘要：Many statistical models for networks overlook the fact that most real-world networks are formed through a growth process. To address this, we introduce the Preferential Attachment Plus Erdos-Renyi model, where we let a random network G be the union of a preferential attachment (PA) tree T and additional Erdos-Renyi (ER) random edges. The PA tree captures the underlying growth process of a network where vertices/edges are added sequentially, while the ER component can be regarded as noise. Give...
• Tianxi Lis contribution to the Discussion of Root and community inference on the latent growth process of a network by Crane and Xu AI翻译
  作者：Li, Tianxi
  作者单位：University of Minnesota System; University of Minnesota Twin Cities
  摘要：Many statistical models for networks overlook the fact that most real-world networks are formed through a growth process. To address this, we introduce the Preferential Attachment Plus Erdos-Renyi model, where we let a random network G be the union of a preferential attachment (PA) tree T and additional Erdos-Renyi (ER) random edges. The PA tree captures the underlying growth process of a network where vertices/edges are added sequentially, while the ER component can be regarded as noise. Give...
• Gilbert MacKenzie's contribution to the Discussion of 'the Discussion Meeting on Probabilistic and statistical aspects of machine learning' AI翻译
  作者：MacKenzie, Gilbert
  作者单位：University of Limerick; Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI)
• Testing many constraints in possibly irregular models using incomplete U-statistics AI翻译
  作者：Sturma, Nils; Drton, Mathias; Leung, Dennis
  作者单位：Technical University of Munich; Technical University of Munich; University of Melbourne; Technical University of Munich
  摘要：We consider the problem of testing a null hypothesis defined by equality and inequality constraints on a statistical parameter. Testing such hypotheses can be challenging because the number of relevant constraints may be on the same order or even larger than the number of observed samples. Moreover, standard distributional approximations may be invalid due to irregularities in the null hypothesis. We propose a general testing methodology that aims to circumvent these difficulties. The constrai...