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作者：Duanmu, Haosui; Roy, Daniel M.; Smith, Aaron
作者单位：Harbin Institute of Technology; University of California System; University of California Berkeley; University of Toronto; University of Ottawa
摘要：A matching prior at level 1 - a is a prior such that an associated 1 - a credible region is also a 1- a confidence set. We study the existence of matching priors for general families of credible regions. Our main result gives topological conditions under which matching priors for specific families of credible regions exist. Informally, we prove that, on compact parameter spaces, a matching prior exists if the so-called rejection-probability function is jointly continuous when we adopt the Wass...
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作者：Guan, Yawen; Page, Garritt L.; Reich, Brian J.; Ventrucci, Massimo; Yang, Shu
作者单位：University of Nebraska System; University of Nebraska Lincoln; Brigham Young University; North Carolina State University; University of Bologna
摘要：Adjusting for an unmeasured confounder is generally an intractable problem, but in the spatial setting it may be possible under certain conditions. We derive necessary conditions on the coherence between the exposure and the unmeasured confounder that ensure the effect of exposure is estimable. We specify our model and assumptions in the spectral domain to allow for different degrees of confounding at different spatial resolutions. One assumption that ensures identifiability is that confoundin...
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作者：Vogrinc, Jure; Livingstone, Samuel; Zanella, Giacomo
作者单位：University of Warwick; University of London; University College London; Bocconi University
摘要：We study the class of first-order locally balanced Metropolis-Hastings algorithms introduced in Livingstone & Zanella (2022). To choose a specific algorithm within the class, the user must select a balancing function g : R+ -> R+ satisfying g(t) = tg(1/t) and a noise distribution for the proposal increment. Popular choices within the class are the Metropolis-adjusted Langevin algorithm and the recently introduced Barker proposal. We first establish a general limiting optimal acceptance rate of...
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作者：Yu, Long; Xie, Jiahui; Zhou, Wang
作者单位：Shanghai University of Finance & Economics; National University of Singapore
摘要：The Kronecker product covariance structure provides an efficient way to model the inter-correlations of matrix-variate data. In this paper, we propose test statistics for the Kronecker product covariance matrix based on linear spectral statistics of renormalized sample covariance matrices. A central limit theorem is proved for the linear spectral statistics, with explicit formulas for the mean and covariance functions, thereby filling a gap in the literature. We then show theoretically that th...
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作者：Guo, Kevin; Rothenhausler, Dominik
作者单位：Stanford University
摘要：In observational causal inference, exact covariate matching plays two statistical roles: (i) it effectively controls for bias due to measured confounding; (ii) it justifies assumption-free inference based on randomization tests. In this paper we show that inexact covariate matching does not always play these same roles. We find that inexact matching often leaves behind statistically meaningful bias, and that this bias renders standard randomization tests asymptotically invalid. We therefore re...
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作者：Shi, J.; Wu, Z.; Dempsey, W.
作者单位：University of Michigan System; University of Michigan
摘要：The micro-randomized trial is a sequential randomized experimental design to empirically evaluate the effectiveness of mobile health intervention components that may be delivered at hundreds or thousands of decision points. Micro-randomized trials have motivated a new class of causal estimands, termed causal excursion effects, for which semiparametric inference can be conducted via a weighted, centred least-squares criterion (Boruvka et al., 2018). Causal excursion effects allow health scienti...
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作者：Schultheiss, C.; Buhlmann, P.
