Journal of the American Statistical Association

最新文章

• Contextual Dynamic Pricing: Algorithms, Optimality, and Local Differential Privacy Constraints AI翻译
  作者：Zhao, Zifeng; Jiang, Feiyu; Yu, Yi
  作者单位：University of Notre Dame; Fudan University; University of Warwick
  摘要：We study contextual dynamic pricing problems where a firm sells products to T sequentially-arriving consumers, behaving according to an unknown demand model. The firm aims to minimize its regret over a clairvoyant that knows the model in advance. The demand follows a generalized linear model (GLM), allowing for stochastic feature vectors in R-d encoding product and consumer information. We first show the optimal regret is of order root dT, up to logarithmic factors, improving existing upper bo...
• Variable Significance Testing for the Deep Cox Model AI翻译
  作者：Zhong, Qixian; Mueller, Jonas; Wang, Jane-Ling
  作者单位：Xiamen University; Xiamen University; University of California System; University of California Davis
  摘要：Deep learning has become enormously popular in the analysis of complex data, including event time measurements with censoring. To date, deep survival methods have mainly focused on prediction. Such methods are scarcely used in matters of statistical inference such as hypothesis testing. Due to their black-box nature, deep-learned outcomes lack interpretability which limits their use for decision-making in biomedical applications. This article provides estimation and inference methods for the n...
• The Impact of Job Stability on Monetary Poverty in Italy: Causal Small Area Estimation AI翻译
  作者：Reluga, Katarzyna; Kong, Dehan; Ranjbar, Setareh; Salvati, Nicola; van der Laan, Mark
  作者单位：Humboldt University of Berlin; University of Toronto; University of Lausanne; Centre Hospitalier Universitaire Vaudois (CHUV); University of Pisa; University of California System; University of California Berkeley
  摘要：Job stability-encompassing secure contracts, adequate wages, social benefits, and career opportunities-is a critical determinant in reducing monetary poverty, as it provides households with reliable income and enhances economic well-being. This study draws on EU-SILC survey and census data to estimate the causal effect of job stability on monetary poverty across Italian provinces, quantifying its influence, and analyzing regional disparities. We introduce a novel causal small area estimation (...
• Covariate-Elaborated Robust Partial Information Transfer with Conditional Spike-and-Slab Prior AI翻译
  作者：Zhang, Ruqian; Zhang, Yijiao; Shen, Juan; Zhu, Zhongyi; Qu, Annie
  作者单位：Fudan University; University of Pennsylvania; Pennsylvania Medicine; University of California System; University of California Santa Barbara
  摘要：The popularity of transfer learning stems from the fact that it can borrow information from useful auxiliary datasets. Existing statistical transfer learning methods usually adopt a global similarity measure between the source data and the target data, which may lead to inefficiency when only partial information is shared. In this article, we propose a novel Bayesian transfer learning method named CONCERT to allow robust partial information transfer for high-dimensional data analysis. A condit...
• Effect Aliasing in Observational Studies AI翻译
  作者：Rosenbaum, Paul R.; Zubizarreta, Jose R.
  作者单位：University of Pennsylvania; Harvard University; Harvard Medical School; Harvard University
  摘要：In experimental design, aliasing of effects occurs in fractional factorial experiments, where certain low order factorial effects are indistinguishable from certain high order interactions: low order contrast weights may be orthogonal to one another, while their higher order interactions are aliased and not identified. In observational studies, aliasing occurs when certain combinations of covariates-for example, time period and various eligibility criteria for treatment-perfectly predict the t...
• Deep Mutual Density Ratio Estimation with Bregman Divergence and Its Applications AI翻译
  作者：Han, Dongxiao; Zheng, Siming; Shen, Guohao; Song, Xinyuan; Sun, Liuquan; Huang, Jian
  作者单位：Nankai University; Nankai University; Chinese University of Hong Kong; Hong Kong Polytechnic University; Chinese Academy of Sciences; Nanjing Institute of Geology & Paleontology, CAS; Academy of Mathematics & System Sciences, CAS; Hong Kong Polytechnic University
  摘要：This article introduces a unified approach to estimating the mutual density ratio, defined as the ratio between the joint density function and the product of the individual marginal density functions of two random vectors. It serves as a fundamental measure for quantifying the relationship between two random vectors. Our method uses the Bregman divergence to construct the objective function and leverages deep neural networks to approximate the logarithm of the mutual density ratio. We establis...
• LAMBDA: A Large Model Based Data Agent AI翻译
  作者：Sun, Maojun; Han, Ruijian; Jiang, Binyan; Qi, Houduo; Sun, Defeng; Yuan, Yancheng; Huang, Jian
  作者单位：Hong Kong Polytechnic University; Hong Kong Polytechnic University; Hong Kong Polytechnic University
  摘要：We introduce LArge Model Based Data Agent (LAMBDA), a novel open-source, code-free multi-agent data analysis system that leverages the power of large language models. LAMBDA is designed to address data analysis challenges in data-driven applications through innovatively designed data agents using natural language. At the core of LAMBDA are two key agent roles: the programmer and the inspector, which are engineered to work together seamlessly. Specifically, the programmer generates code based o...
• Rate-Optimal Rank Aggregation with Private Pairwise Rankings AI翻译
  作者：Xu, Shirong; Sun, Will Wei; Cheng, Guang
  作者单位：University of California System; University of California Los Angeles; Purdue University System; Purdue University
  摘要：In various real-world scenarios, such as recommender systems and political surveys, pairwise rankings are commonly collected and used for rank aggregation to derive an overall ranking of items. However, preference rankings can reveal individuals' personal preferences, highlighting the need to protect them from exposure in downstream analysis. In this article, we address the challenge of preserving privacy while ensuring the utility of rank aggregation based on pairwise rankings generated from ...
• Estimation and Inference of Quantile Spatially Varying Coefficient Models Over Complicated Domains AI翻译
  作者：Kim, Myungjin; Wang, Lily; Wang, Huixia Judy
  作者单位：Kyungpook National University (KNU); George Mason University; George Washington University
  摘要：This article presents a flexible quantile spatially varying coefficient model (QSVCM) for the regression analysis of spatial data. The proposed model enables researchers to assess the dependence of conditional quantiles of the response variable on covariates while accounting for spatial nonstationarity. Our approach facilitates learning and interpreting heterogeneity in spatial data distributed over complex or irregular domains. We introduce a quantile regression method that uses bivariate pen...
• Large Precision Matrix Estimation with Unknown Group Structure AI翻译
  作者：Cheng, Cong; Ke, Yuan; Zhang, Wenyang
  作者单位：University System of Georgia; University of Georgia; University of Macau
  摘要：The estimation of large precision matrices is crucial in modern multivariate analysis. Traditional sparsity assumptions, while useful, often fall short of accurately capturing the dependencies among features. This article addresses this limitation by focusing on precision matrix estimation for multivariate data characterized by a flexible yet unknown group structure. We introduce a novel approach that begins with the detection of this unknown group structure, clustering features within the low...