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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：Xue, HQ; Lam, KF; Li, GY
作者单位：Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; University of Hong Kong; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS
摘要：In a randomized controlled clinical trial study where the response variable of interest is the time to occurrence of a certain event, it is often too expensive or even impossible to observe the exact time. However, the current status of the subject at a random time of inspection is much more natural, feasible, and practical in terms of cost-effectiveness. This article considers a semiparametric regression model that consists of parametric and nonparametric regression components. A sieve maximu...
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作者：King, R; Brooks, SP
作者单位：University of St Andrews; University of Cambridge
摘要：Effective management is the key to the protection of many endangered species. Identification of the primary factors that affect their survival often lead to L introduction of strategies to improve survival rates. In this article, we consider a small population of Hector's dolphins located off the coast of New Zealand and the impact that the establishment of a seasonal sanctuary has on their survival and migration rates. Using Akaike's information criterion and an extension of the simulated ann...
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作者：Chen, HY
作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
摘要：Robustness of covariate modeling for the missing-covariate problem in parametric regression is studied under the missing-at-random assumption. For a simple missing-covariate pattern, nonparametric covariate model is proposed and is shown to yield a consistent and semiparametrically efficient estimator for the regression parameter, Total robustness is achieved in this situation. For more general missing-covariate patterns, a novel semiparametric modeling approach is proposed for the covariates....
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作者：Hall, P; Racine, J; Li, Q
作者单位：Australian National University; Syracuse University; Syracuse University; Texas A&M University System; Texas A&M University College Station
摘要：Many practical problems, especially some connected with forecasting, require nonparametric estimation of conditional densities from mixed data. For example, given an explanatory data vector X for a prospective customer, with components that could include the customer's salary, occupation, age, sex, marital status, and address, a company might wish to estimate the density of the expenditure, Y, that could be made by that person, basing the inference on observations of (X, Y) for previous client...
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作者：Hubert, M; Rousseeuw, PJ; Branden, KV
作者单位：KU Leuven; University of Antwerp; KU Leuven
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作者：Müller, P; Parmigiani, G; Robert, C; Rousseau, J
作者单位：University of Texas System; UTMD Anderson Cancer Center; Johns Hopkins University; Universite PSL; Universite Paris-Dauphine; Institut Polytechnique de Paris; ENSAE Paris; Universite Paris Cite
摘要：We consider the choice of an optimal sample size for multiple-comparison problems. The motivating application is the choice of the number of microarray experiments to be carried out when learning about differential gene expression. However, the approach is valid in any application that involves multiple comparisons in a large number of hypothesis tests. We discuss two decision problems in the context of this setup: the. sample size selection and the decision about the multiple comparisons. We ...
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作者：Hu, CC; Lin, DY
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; University of North Carolina; University of North Carolina Chapel Hill
摘要：This article proposes a general strategy for the regression analysis of univariate and multivariate failure time data when a subset of covariates cannot be measured precisely but replicate measurements of their surrogates are available. Multivariate failure time data include recurrent events and clustered Survival data. The number of replicate measurements can vary from subject to subject and can even depend on the failure time. No parametric assumption is imposed on the error or on any other ...
