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作者：Savchuk, Olga Y.; Hart, Jeffrey D.; Sheather, Simon J.
作者单位：State University of New York (SUNY) System; Binghamton University, SUNY; Texas A&M University System; Texas A&M University College Station
摘要：A new method of bandwidth selection or kernel density estimators is proposed The method termed indirect cross-validation (ICY). makes use of so-called selection kernels Least-squares cross-validation (LSCV) is used to select the bandwidth of a selection-kernel estimator and this bandwidth is appropriately escaled for use in a Gaussian kernel estimator The proposed selection kernels are linear combinations of two Gaussian kennels and need not be unimodal or positive A theory is developed showin...
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作者：Berrocal, Veronica J.; Raftery, Adrian E.; Gneiting, Tilmann; Steed, Richard C.
作者单位：University of Washington; University of Washington Seattle; Ruprecht Karls University Heidelberg; University of Washington; University of Washington Seattle
摘要：Winter road maintenance is one of the main tasks for the Washington State Department of Transportation. Anti-icing, that is, the preemptive application of chemicals, is often used to keep the roadways free of ice. Given the preventive nature of anti-icing, accurate predictions of road ice are needed. Currently, anti-icing decisions are usually based on deterministic weather forecasts. However, the costs of the two kinds of errors are highly asymmetric because the cost of a road closure due to ...
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作者：Efromovich, Sam
作者单位：University of Texas System; University of Texas Dallas
摘要：An orthogonal series estimator of the conditional density of a response given a vector of continuous and ordinal/nominal categorical predictors is suggested. The estimator is based on writing a conditional density as a sum of orthogonal projections on all possible subspaces of reduced dimensionality and then estimating each projection via a shrinkage procedure. The shrinkage procedure uses a universal thresholding and a dyadic-blockwise shrinkage for low and high frequencies, respectively. The...
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作者：Guha, Subharup
作者单位：University of Missouri System; University of Missouri Columbia
摘要：Mixture models, or convex combinations of a countable number of probability distributions, offer an elegant framework for inference when the population of interest can be subdivided into latent clusters having random characteristics that are heterogeneous between, but homogeneous within, the clusters. Traditionally, the different kinds of mixture models have been motivated and analyzed from very different perspectives, and their common characteristics have not been fully appreciated. The infer...
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作者：Li, Chun; Shepherd, Bryan E.
作者单位：Vanderbilt University
摘要：We propose a new set of test statistics to examine the association between two ordinal categorical variables X and Y after adjusting for continuous and/or categorical covariates Z. Our approach first fits multinomial (e.g.. proportional odds) models of X and Y, separately, on Z. For each subject, we then compute the conditional distributions of X and Y given Z. If there is no relationship between X and Y after adjusting for Z. then these conditional distributions will be independent, and the o...
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作者：Diggle, Peter J.; Guan, Yongtao; Hart, Anthony C.; Paize, Fauzia; Stanton, Michelle
作者单位：Yale University; Lancaster University; Johns Hopkins University; Alder Hey Children's NHS Foundation Trust; University of Liverpool; University of Liverpool
摘要：We propose a novel alternative to case-control sampling for the estimation of individual-level risk in spatial epidemiology. Our approach uses weighted estimating equations to estimate regression parameters in the intensity function of an inhomogeneous spatial point process, when information on risk-factors is available at the individual level for cases, but only at a spatially aggregated level for the population at risk. We develop data-driven methods to select the weights used in the estimat...
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作者：Gneiting, Tilmann; Kleiber, William; Schlather, Martin
作者单位：Ruprecht Karls University Heidelberg; University of Washington; University of Washington Seattle; University of Gottingen
摘要：We introduce a flexible parametric family of matrix-valued covariance functions for multivariate spatial random fields, where each constituent component is a Matern process. The model parameters are interpretable in terms of process variance, smoothness, correlation length, and colocated correlation coefficients, which can be positive or negative. Both the marginal and the cross-covariance functions are of the Matern type. In a data example on error fields for numerical predictions of surface ...
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作者：Schwartzman, Armin
作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute
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作者：Tarpey, Thaddeus; Petkova, Eva; Lu, Yimeng; Govindarajulu, Usha
作者单位：University System of Ohio; Wright State University Dayton; New York University; Novartis; Novartis USA; Harvard University; Harvard University Medical Affiliates; Brigham & Women's Hospital
摘要：A longstanding problem in clinical research is distinguishing drug-treated subjects that respond due to specific effects of the drug from those that respond to nonspecific (or placebo) effects of the treatment. Linear mixed effect models are commonly used to model longitudinal clinical trial data. In this paper we present a solution to the problem of identifying placebo responders using an optimal partitioning methodology for linear mixed effects models. Since individual outcomes in a longitud...
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作者：Glynn, Adam N.; Richardson, Thomas S.; Handcock, Mark S.
作者单位：Harvard University; University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle
摘要：In close elections, the losing side has an incentive to obtain evidence that the election result is incorrect Sometimes this evidence comes in the form of court testimony from a sample of invalid voters, and this testimony is used to adjust vote totals (Belcher v Mayor of Ann Arbor 1978, Borders v King County 2005) However, while courts may be reluctant to make explicit findings about out-of-sample data (e g Invalid voters that do not testify), when samples are used to adjust vote totals. the ...
