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作者：Ludkin, M.; Sherlock, C.
作者单位：Lancaster University
摘要：This article introduces the hug and hop Markov chain Monte Carlo algorithm for estimating expectations with respect to an intractable distribution. The algorithm alternates between two kernels, referred to as hug and hop. Hug is a nonreversible kernel that repeatedly applies the bounce mechanism from the recently proposed bouncy particle sampler to produce a proposal point that is far from the current position yet on almost the same contour of the target density, leading to a high acceptance p...
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作者：Yan, Jian; Zhang, Xianyang
作者单位：Texas A&M University System; Texas A&M University College Station
摘要：Motivated by the increasing use of kernel-based metrics for high-dimensional and large-scale data, we study the asymptotic behaviour of kernel two-sample tests when the dimension and sample sizes both diverge to infinity. We focus on the maximum mean discrepancy using an isotropic kernel, which includes maximum mean discrepancy with the Gaussian kernel and the Laplace kernel, and the energy distance as special cases. We derive asymptotic expansions of the kernel two-sample statistics, based on...
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作者：Yu, Miao; Lu, Wenbin; Yang, Shu; Ghosh, Pulak
作者单位：North Carolina State University; Indian Institute of Management (IIM System); Indian Institute of Management Bangalore
摘要：Zero-inflated nonnegative outcomes are common in many applications. In this work, motivated by freemium mobile game data, we propose a class of multiplicative structural nested mean models for zero-inflated nonnegative outcomes which flexibly describes the joint effect of a sequence of treatments in the presence of time-varying confounders. The proposed estimator solves a doubly robust estimating equation, where the nuisance functions, namely the propensity score and conditional outcome means ...
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作者：Dunn, Robin; Ramdas, Aaditya; Balakrishnan, Sivaraman; Wasserman, Larry
作者单位：Novartis; Novartis USA; Carnegie Mellon University
摘要：The classical likelihood ratio test based on the asymptotic chi-squared distribution of the log-likelihood is one of the fundamental tools of statistical inference. A recent universal likelihood ratio test approach based on sample splitting provides valid hypothesis tests and confidence sets in any setting for which we can compute the split likelihood ratio statistic, or, more generally, an upper bound on the null maximum likelihood. The universal likelihood ratio test is valid in finite sampl...
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作者：Zhou, Zheng; Zhou, Yongdao
作者单位：Nankai University
摘要：Row-column designs have been widely used in experiments involving double confounding. Among them, one that provides unconfounded estimation of all main effects and as many two-factor interactions as possible is preferred, and is called optimal. Most current work focuses on the construction of two-level row-column designs, while the corresponding optimality theory has been largely ignored. Moreover, most constructed designs contain at least one replicate of a full factorial design, which is not...
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作者：Lin, Z.; Han, F.
作者单位：University of Washington; University of Washington Seattle
摘要：The ingenious approach of Chatterjee (2021) to estimate a measure of dependence first proposed by Dette et al. (2013) based on simple rank statistics has quickly caught attention. This measure of dependence has the appealing property of being between 0 and 1, and being 0 or 1 if and only if the corresponding pair of random variables is independent or one is a measurable function of the other almost surely. However, more recent studies (Cao & Bickel 2020; Shi et al. 2022b) showed that independe...
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作者：Qiu, Yixuan; Lei, Jing; Roeder, Kathryn
作者单位：Shanghai University of Finance & Economics; Carnegie Mellon University
摘要：Sparse principal component analysis is an important technique for simultaneous dimensionality reduction and variable selection with high-dimensional data. In this work we combine the unique geometric structure of the sparse principal component analysis problem with recent advances in convex optimization to develop novel gradient-based sparse principal component analysis algorithms. These algorithms enjoy the same global convergence guarantee as the original alternating direction method of mult...
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作者：Lin, Z.; Muller, H. G.; Park, B. U.
作者单位：National University of Singapore; University of California System; University of California Davis; Seoul National University (SNU)
摘要：We propose and investigate an additive regression model for symmetric positive-definite matrix-valued responses and multiple scalar predictors. The model exploits the Abelian group structure inherited from either of the log-Cholesky and log-Euclidean frameworks for symmetric positive-definite matrices and naturally extends to general Abelian Lie groups. The proposed additive model is shown to connect to an additive model on a tangent space. This connection not only entails an efficient algorit...
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作者：Lu, Zitong; Geng, Zhi; Li, Wei; Zhu, Shengyu; Jia, Jinzhu
作者单位：Peking University; Beijing Technology & Business University; Renmin University of China; Renmin University of China; Huawei Technologies; Peking University; Peking University
摘要：For the case with a single causal variable, Dawid et al. (2014) defined the probability of causation, and Pearl (2000) defined the probability of necessity to assess the causes of effects. For a case with multiple causes that could affect each other, this paper defines the posterior total and direct causal effects based on the evidence observed for post-treatment variables, which could be viewed as measurements of causes of effects. Posterior causal effects involve the probabilities of counter...
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作者：Liu, Hanzhong; Tu, Fuyi; Ma, Wei
作者单位：Tsinghua University; Renmin University of China
摘要：We consider the problem of estimating and inferring treatment effects in randomized experiments. In practice, stratified randomization, or more generally, covariate-adaptive randomization, is routinely used in the design stage to balance treatment allocations with respect to a few variables that are most relevant to the outcomes. Then, regression is performed in the analysis stage to adjust the remaining imbalances to yield more efficient treatment effect estimators. Building upon and unifying...
