-
作者：Martin, Ryan
作者单位：North Carolina State University
摘要：We derive confidence intervals (CIs) and confidence sequences (CSs) for the classical problem of estimating a bounded mean. Our approach generalizes and improves on the celebrated Chernoff method, yielding the best closed-form empirical-Bernstein CSs and CIs (converging exactly to the oracle Bernstein width) as well as non-closed-form betting CSs and CIs. Our method combines new composite nonnegative (super) martingales with Ville's maximal inequality, with strong connections to testing by bet...
-
作者：Zheng, Xiangyu; Chen, Song Xi
作者单位：Peking University; Peking University; Peking University; Peking University
摘要：Motivated by evaluating the effects of air pollution alerts on air quality, we propose the dynamic synthetic control method for micro-level data with time-varying confounders and spatial dependence under an auto-regressive model setting. We employ the empirical likelihood to define the synthetic control weights, which ensures a unique solution and permits theoretical analysis. The dynamic matching increases the feasibility of matching and enables us to assess the unconfoundedness assumption us...
-
作者：Mulder, Joris
作者单位：Tilburg University
-
作者：Li, Jie; Fearnhead, Paul; Fryzlewicz, Piotr; Wang, Tengyao
作者单位：University of London; London School Economics & Political Science; Lancaster University
-
作者：Grunwald, Peter; de Heide, Rianne; Koolen, Wouter
作者单位：Leiden University; Leiden University - Excl LUMC; Vrije Universiteit Amsterdam; University of Twente
摘要：We develop the theory of hypothesis testing based on the e -value, a notion of evidence that, unlike the p -value, allows for effortlessly combining results from several studies in the common scenario where the decision to perform a new study may depend on previous outcomes. Tests based on e -values are safe, i.e. they preserve type-I error guarantees, under such optional continuation. We define growth rate optimality (GRO) as an analogue of power in an optional continuation context, and we sh...
-
作者：Battey, Heather S.
作者单位：Imperial College London
-
作者：Liu, Yaowu; Liu, Zhonghua; Lin, Xihong
作者单位：Southwestern University of Finance & Economics - China; Columbia University; Harvard University; Harvard University; Harvard University; Harvard T.H. Chan School of Public Health
摘要：Testing a global null is a canonical problem in statistics and has a wide range of applications. In view of the fact that no uniformly most powerful test exists, prior and/or domain knowledge are commonly used to focus on a certain class of alternatives to improve the testing power. However, it is generally challenging to develop tests that are particularly powerful against a certain class of alternatives. In this paper, motivated by the success of ensemble learning methods for prediction or c...
-
作者：Kowal, Daniel R.; Matteson, David S.; Ruppert, David
作者单位：Cornell University
-
作者：Cremaschi, Andrea; Wertz, Timothy M.; De Iorio, Maria
作者单位：IE University; National University of Singapore; National University of Singapore; Agency for Science Technology & Research (A*STAR)
摘要：Mixture models are commonly used in applications with heterogeneity and overdispersion in the population, as they allow the identification of subpopulations. In the Bayesian framework, this entails the specification of suitable prior distributions for the weights and locations of the mixture. Despite their popularity, the flexibility of these models often does not translate into the interpretability of the clusters. To overcome this issue, repulsive mixture models have been recently proposed. ...
-
作者：Srakar, Andrej
作者单位：University of Ljubljana
