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作者：Rosenbaum, Paul R.
作者单位：University of Pennsylvania
摘要：In an observational block design, there are I blocks of J individuals, typically with one treated individual and J-1 controls; however, unlike a randomized block design, individuals were not randomly assigned to treatment or control. To be convincing, an observational block design must demonstrate that an ostensible treatment effect is not actually a consequence of small or moderate unmeasured biases of treatment assignment in the absence of a treatment effect. It is known that weighting to ig...
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作者：Borgonovo, Emanuele; Figalli, Alessio; Ghosal, Promit; Plischke, Elmar; Savare, Giuseppe
作者单位：Bocconi University; Bocconi University; ETH Zurich; Swiss Federal Institutes of Technology Domain; ETH Zurich; University of Chicago; Helmholtz Association; Helmholtz-Zentrum Dresden-Rossendorf (HZDR)
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作者：Zhang, Chenlin; Zhou, Ling; Guo, Bin; Lin, Huazhen
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作者：Yang, Shu; Ding, Peng
作者单位：North Carolina State University; University of California System; University of California Berkeley
摘要：Rejective sampling improves design and estimation efficiency of single-phase sampling when auxiliary information in a finite population is available. When such auxiliary information is unavailable, we propose to use two-phase rejective sampling (TPRS), which involves measuring auxiliary variables for the sample of units in the first phase, followed by the implementation of rejective sampling for the outcome in the second phase. We explore the asymptotic design properties of double expansion an...
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作者：Jin, Ying; Ren, Zhimei
作者单位：Harvard University; University of Pennsylvania
摘要：Conformal prediction builds marginally valid prediction intervals that cover the unknown outcome of a randomly drawn test point with a prescribed probability. However, in practice, data-driven methods are often used to identify specific test unit(s) of interest, requiring uncertainty quantification tailored to these focal units. In such cases, marginally valid conformal prediction intervals may fail to provide valid coverage for the focal unit(s) due to selection bias. This article presents a ...
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作者：Zhang, Chenlin; Zhou, Ling; Guo, Bin; Lin, Huazhen
作者单位：Southwestern University of Finance & Economics - China; Southwestern University of Finance & Economics - China
摘要：We develop a Spatial Effect Detection Regression (SEDR) model to capture the nonlinear and irregular effects of high-dimensional spatio-temporal predictors on a scalar outcome. Specifically, we assume that both the component and the coefficient functions in the SEDR are unknown smooth functions of location and time. This allows us to leverage spatially and temporally correlated information, transforming the curse of dimensionality into a blessing, as confirmed by our theoretical and numerical ...
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作者：Beraha, Mario; Argiento, Raffaele; Camerlenghi, Federico; Guglielmi, Alessandra
作者单位：University of Milano-Bicocca; University of Bergamo; Polytechnic University of Milan
摘要：The study of almost surely discrete random probability measures is an active line of research in Bayesian non-parametrics. The idea of assuming interaction across the atoms of the random probability measure has recently spurred significant interest in the context of Bayesian mixture models. This allows the definition of priors that encourage well-separated and interpretable clusters. In this work, we provide a unified framework for the construction and the Bayesian analysis of random probabili...
