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作者：Imai, K; van Dyk, DA
作者单位：Princeton University; University of California System; University of California Irvine
摘要：In this article we develop the theoretical properties of the propensity function, which is a generalization of the propensity score of Rosenbaum and Rubin. Methods based on the propensity score have long been used for causal inference in observational studies; they are easy to use and can effectively reduce the bias caused by nonrandom treatment assignment. Although treatment regimes need not be binary in practice, the propensity score methods are generally confined to binary treatment scenari...
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作者：Li, Y; Ryan, L
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute
摘要：This article is motivated by a time-to-event analysis where the covariate of interest was measured at the wrong time. We show that the problem can be formulated as a special case of survival analysis with heterogeneous covariate measurement error and develop a general analytic framework. We study the asymptotic behavior of the naive partial likelihood estimates and analytically demonstrate that under the heterogeneous measurement error structure and the assumption that all components of the co...
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作者：Briggs, W
作者单位：Cornell University; Weill Cornell Medicine
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作者：Singpurwalla, ND; Booker, JM
作者单位：George Washington University; United States Department of Energy (DOE); Los Alamos National Laboratory
摘要：The notion of fuzzy sets has proven useful in the context of control theory, pattern recognition, and medical diagnosis. However, it has also spawned the view that classical probability theory is unable to deal with uncertainties in natural language and machine learning, so that alternatives to probability are needed. One such alternative is what is known as possibility theory. Such alternatives have come into being because past attempts at making fuzzy set theory and probability theory work i...
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作者：Huang, HY; Ombao, H; Stoffer, DS
作者单位：Fu Jen Catholic University; University of Illinois System; University of Illinois Urbana-Champaign; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
摘要：Statistical discrimination for nonstationary random processes is important in many applications. Our goal was to develop a discriminant scheme that can extract local features of the time series, is consistent, and is computationally efficient. Here, we propose a discriminant scheme based on the SLEX (smooth localized complex exponential) library. The SLEX library forms a collection of Fourier-type bases that are simultaneously orthogonal and localized in both time and frequency domains. Thus, ...
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作者：Carroll, RJ; Ruppert, D; Crainiceanu, CM; Tosteson, TD; Karagas, MR
作者单位：Texas A&M University System; Texas A&M University College Station; Cornell University; Johns Hopkins University; Dartmouth College
摘要：We consider regression when the predictor is measured with error and an instrumental variable (TV) is available. The regression function., or nonparametrically. Our major new result shows that the regression function and all parameters in can be modeled linearly, nonlinearly the measurement error model are identified under relatively weak conditions, much weaker than previously known to imply identifiability. In addition, we exploit a characterization of the IV estimator as a classical correct...
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作者：Gel, Y; Raftery, AE; Gneiting, T
作者单位：George Washington University; University of Washington; University of Washington Seattle
摘要：Probabilistic weather forecasting consists of finding a joint probability distribution for future weather quantities or events. It is typically done by using a numerical weather prediction model, perturbing the inputs to the model in various ways, and running the model for each perturbed set of inputs. The result is then viewed as an ensemble of forecasts, taken to be a sample from the joint probability distribution of the future weather quantities of interest. This is typically not feasible f...
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作者：Shen, XT; Huang, HC; Ye, J
作者单位：University of Minnesota System; University of Minnesota Twin Cities; City University of New York (CUNY) System; Baruch College (CUNY)
摘要：Typical modeling strategies involve model selection, which has a significant effect on inference of estimated parameters. Common practice is to use a selected model ignoring uncertainty introduced by the process of model selection. This could yield overoptimistic inferences, resulting in false discovery. In this article we develop a general methodology via optimal approximation for estimating the mean and variance of complex statistics that involve the process of model selection. This allows u...
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作者：Denby, L; Landwehr, JM; Mallows, CL
作者单位：Avaya
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作者：Liu, XL; Müller, HG
作者单位：University of California System; University of California Los Angeles; University of California Los Angeles Medical Center; David Geffen School of Medicine at UCLA; University of California System; University of California Los Angeles; University of California Los Angeles Medical Center; David Geffen School of Medicine at UCLA; University of California System; University of California Davis
摘要：Data that can be best described as a sample of curves are now fairly common in science and engineering. When the dynamics of development, growth, or response over time are at issue, subjects or experimental units may experience events at different temporal paces. For functional data where trajectories may be individually time-transformed, it is usually inadequate to use commonly used sample statistics, such as the cross-sectional mean or median or the cross-sectional sample variance. If one ob...
