-
作者：Boulin, Alexis; Di Bernardino, Elena; Laloe, Thomas; Toulemonde, Gwladys
作者单位：Centre National de la Recherche Scientifique (CNRS); Universite Cote d'Azur; Inria; Universite de Montpellier; Centre National de la Recherche Scientifique (CNRS)
摘要：We propose a new class of models for variable clustering called Asymptotic Independent block (AI-block) models, which defines population-level clusters based on the independence of the maxima of a multivariate stationary mixing random process among clusters. This class of models is identifiable, meaning that there exists a maximal element with a partial order between partitions, allowing for statistical inference. We also present an algorithm depending on a tuning parameter that recovers the c...
-
作者：Oyet, Alwell; Sutradhar, Brajendra C.; Rao, R. Prabhakar
作者单位：Memorial University Newfoundland; Sri Sathya Sai Institute of Higher Learning
摘要：In this article we propose a general multinomial dynamic mixed logits model which explains how a multinomial/categorical response at a given time can be affected by (a) an individual's categorical fixed covariates, (b) certain category prone random effects, and (c) an individual's past multinomial responses. This model may be considered as a generalization of the (a) existing multinomial dynamic fixed models to the mixed model setup with category prone random effects; or (b) existing standard ...
-
作者：Uematsu, Yoshimasa; Yamagata, Takashi
作者单位：Hitotsubashi University; University of York - UK; University of Osaka
摘要：This article proposes novel inferential procedures for discovering the network Granger causality in high-dimensional vector autoregressive models. In particular, we mainly offer two multiple testing procedures designed to control the false discovery rate (FDR). The first procedure is based on the limiting normal distribution of the t-statistics with the debiased lasso estimator. The second procedure is its bootstrap version. We also provide a robustification of the first procedure against any ...
-
作者：Yu, Myeonghun; Wang, Yue; Xie, Siyu; Tan, Kean Ming; Zhou, Wen-Xin
作者单位：University of Michigan System; University of Michigan; Chinese Academy of Sciences; University of Science & Technology of China, CAS; Northwestern University; University of Michigan System; University of Michigan; University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
摘要：Expected shortfall (ES) has emerged as an important metric for characterizing the tail behavior of a random outcome, specifically associated with rarer events that entail severe consequences. In climate science, the threats of flooding and heatwaves loom large, impacting natural environments and human communities. In actuarial studies, a key observation in modeling insurance claim sizes is that features exhibit distinct effects in explaining small and large claims. This article concerns nonpar...
-
作者：Iannario, Maria; Dasgupta, Nairanjana; Morrison, Jillian; Raton, Boca
-
作者：Fry, Kevin; Panigrahi, Snigdha; Taylor, Jonathan
作者单位：Stanford University; University of Michigan System; University of Michigan
-
作者：Liao, Yuan; Todorov, Viktor
摘要：We test for temporal stability in local linear projection coefficients of observable factors on latent ones embedded in a high-dimensional vector obeying a linear factor model. The proposed test explores the fact that, under the null hypothesis, residuals from global linear projections of observable factors on latent ones, computed over a fixed time interval via Principal Component Analysis (PCA), should also be locally uncorrelated with the PCA factors. The test is fully nonparametric. Its as...
-
作者：Wu, Peikai; Xiao, Zhiguo
作者单位：Fudan University
摘要：We introduce a novel framework for causal inference in dynamic panel data that extends the cross-sectional Double/Debiased Machine Learning (DML) approach. The method rests on a partially linear dynamic panel model with two-way fixed effects for potential outcomes and readily accommodates binary, multi-valued, or continuous treatments. To translate potential outcome models into an estimable form, we introduce dynamic conditional independence assumptions. By integrating cross-fitting, the nonpa...
-
作者：Dalla Pria, Marco; Ruggiero, Matteo; Spano, Dario
作者单位：University of Turin; New York University; New York University Abu Dhabi; University of Warwick
摘要：We introduce a nonparametric model for inferring time-evolving, unobserved probability distributions from discrete-time data consisting of unlabelled partitions. The latent process is a two-parameter Poisson-Dirichlet diffusion, and observations arise via exchangeable sampling. Applications include social and genetic data where only aggregate clustering summaries are observed. To address the intractable likelihood, we develop a tractable inferential framework that avoids label enumeration and ...
-
作者：Liang, Ruiting; Zhu, Wanrong; Barber, Rina Foygel
作者单位：University of Chicago; University of California System; University of California Irvine; University of Chicago
摘要：Given a family of pretrained models and a hold-out set, how can we construct a valid conformal prediction set while selecting a model that minimizes the width of the set? If we use the same hold-out dataset both to select a model (the model that yields the smallest conformal prediction sets) and then to construct a conformal prediction set based on that selected model, we suffer a loss of coverage due to selection bias. Alternatively, we could further split the data to perform selection and ca...
