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作者：Zhu, Changbo; Muller, Hans-Georg
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作者：Thams, Nikolaj; Saengkyongam, Sorawit; Pfister, Niklas; Peters, Jonas
作者单位：University of Copenhagen
摘要：We introduce statistical testing under distributional shifts. We are interested in the hypothesis P*? H(0 )for a target distribution P*, but observe data from a different distribution Q*. We assume that P* is related to Q* through a known shift t and formally introduce hypothesis testing in this setting. We propose a general testing procedure that first resamples from the observed data to construct an auxiliary data set (similarly to sampling importance resampling) and then applies an existing...
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作者：Zhu, Changbo; Mueller, Hans-Georg
作者单位：University of Notre Dame; University of California System; University of California Davis
摘要：Series of univariate distributions indexed by equally spaced time points are ubiquitous in applications and their analysis constitutes one of the challenges of the emerging field of distributional data analysis. To quantify such distributional time series, we propose a class of intrinsic autoregressive models that operate in the space of optimal transport maps. The autoregressive transport models that we introduce here are based on regressing optimal transport maps on each other, where predict...
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作者：Yu, Weichang; Bondell, Howard D.
作者单位：University of Melbourne
摘要：Clinicians often make sequences of treatment decisions that can be framed as dynamic treatment regimes. In this paper, we propose a Bayesian likelihood-based dynamic treatment regime model that incorporates regression specifications to yield interpretable relationships between covariates and stage-wise outcomes. We define a set of probabilistically-coherent properties for dynamic treatment regime processes and present the theoretical advantages that are consequential to these properties. We ju...
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作者：Evans, Robin J.; Didelez, Vanessa
作者单位：University of Oxford; Leibniz Association; Leibniz Institute for Prevention Research & Epidemiology (BIPS); University of Bremen; University of Bremen
摘要：Many statistical problems in causal inference involve a probability distribution other than the one from which data are actually observed; as an additional complication, the object of interest is often a marginal quantity of this other probability distribution. This creates many practical complications for statistical inference, even where the problem is non-parametrically identified. In particular, it is difficult to perform likelihood-based inference, or even to simulate from the model in a ...
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作者：Zhu, Changbo; Wang, Jane-Ling
作者单位：University of Notre Dame; University of California System; University of California Davis
摘要：Testing the homogeneity between two samples of functional data is an important task. While this is feasible for intensely measured functional data, we explain why it is challenging for sparsely measured functional data and show what can be done for such data. In particular, we show that testing the marginal homogeneity based on point-wise distributions is feasible under some mild constraints and propose a new two-sample statistic that works well with both intensively and sparsely measured func...
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作者：Berenguer-Rico, Vanessa; Johansen, Soren; Nielsen, Bent
作者单位：University of Oxford; University of Copenhagen; University of Oxford
摘要：The least trimmed squares (LTS) estimator is a popular robust regression estimator. It finds a subsample of h 'good' observations among n observations and applies least squares on that subsample. We formulate a model in which this estimator is maximum likelihood. The model has 'outliers' of a new type, where the outlying observations are drawn from a distribution with values outside the realized range of h 'good', normal observations. The LTS estimator is found to be h(1/2) consistent and asym...
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作者：Bennett, Andrew; Kallus, Nathan
作者单位：Cornell University; Cornell University
摘要：The conditional moment problem is a powerful formulation for describing structural causal parameters in terms of observables, a prominent example being instrumental variable regression. We introduce a very general class of estimators called the variational method of moments (VMM), motivated by a variational minimax reformulation of optimally weighted generalized method of moments for finite sets of moments. VMM controls infinitely for many moments characterized by flexible function classes suc...
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作者：Yang, Liuqing; Zhou, Yongdao; Liu, Min-Qian
作者单位：Nankai University; Nankai University
摘要：In many practical experiments, both the level combinations of factors and the addition orders will affect the responses. However, virtually no construction methods have been provided for such experimental designs. This paper focuses on such experiments, introduces a new type of design called the ordering factorial design, and proposes the nominal main effect component-position model and interaction-main effect component-position model. To obtain efficient fractional designs, we provide some de...
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作者：Wu, Sanyou; Feng, Long
作者单位：University of Hong Kong
摘要：This paper aims to present the first Frequentist framework on signal region detection in high-resolution and high-order image regression problems. Image data and scalar-on-image regression are intensively studied in recent years. However, most existing studies on such topics focussed on outcome prediction, while the research on region detection is rather limited, even though the latter is often more important. In this paper, we develop a general framework named Sparse Kronecker Product Decompo...
