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作者：Ni, LQ; Cook, RD; Tsai, CL
作者单位：State University System of Florida; University of Central Florida; University of Minnesota System; University of Minnesota Twin Cities; University of California System; University of California Davis
摘要：We employ Lasso shrinkage within the context of sufficient dimension reduction to obtain a shrinkage sliced inverse regression estimator, which provides easier interpretations and better prediction accuracy without assuming a parametric model. The shrinkage sliced inverse regression approach can be employed for both single-index and multiple-index models. Simulation studies suggest that the new estimator performs well when its tuning parameter is selected by either the Bayesian information cri...
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作者：Sweeting, TJ
作者单位：University of London; University College London
摘要：Probability matching priors are priors for which the posterior probabilities of certain specified sets are exactly or approximately equal to their coverage probabilities. These priors arise as solutions of partial differential equations that may be difficult to solve, either analytically or numerically. Recently Levine & Casella (2003) presented an algorithm for the implementation of probability matching priors for an interest parameter in the presence of a single nuisance parameter. In this p...
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作者：Zhang, H; Zimmerman, DL
作者单位：Washington State University; University of Iowa
摘要：Two asymptotic frameworks, increasing domain asymptotics and infill asymptotics, have been advanced for obtaining limiting distributions of maximum likelihood estimators of covariance parameters in Gaussian spatial models with or without a nugget effect. These limiting distributions are known to be different in some cases. It is therefore of interest to know, for a given finite sample, which framework is more appropriate. We consider the possibility of making this choice on the basis of how we...
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作者：Allen, AS; Satten, GA; Tsiatis, AA
作者单位：Duke University; Duke University; Centers for Disease Control & Prevention - USA; North Carolina State University
摘要：Modelling human genetic variation is critical to understanding the genetic basis of complex disease. The Human Genome Project has discovered millions of binary DNA sequence variants, called single nucleotide polymorphisms, and millions more may exist. As coding for proteins takes place along chromosomes, organisation of polymorphisms along each chromosome, the haplotype phase structure, may prove to be most important in discovering genetic variants associated with disease. As haplotype phase i...
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作者：Ritz, C; Skovgaard, IM
作者单位：University of Copenhagen
摘要：For submodels of an exponential family, we consider likelihood ratio tests for hypotheses that render some parameters nonidentifiable. First, we establish the asymptotic equivalence between the likelihood ratio test and the score test. Secondly, the score-test representation is used to derive the asymptotic distribution of the likelihood ratio test. These results are derived for general submodels of an exponential family without assuming compactness of the parameter space. We then exemplify th...
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作者：Marshall, AW; Olkin, I
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作者：Cheung, YK
作者单位：Columbia University
摘要：This paper studies the coherence conditions of dose-finding methods in the context of phase I clinical trials, where the objective is to estimate a targeted quantile of the unknown dose-toxicity curve. Most phase I methods are outcome-adaptive, and thus escalate or de-escalate doses for future patients based on the previous observations. An escalation for a new patient is said to be coherent only when the previous patient does not show sign of toxicity. Likewise, a de-escalation is coherent on...
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作者：Lam, KF; Xue, HQ
作者单位：University of Hong Kong; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS
摘要：This paper considers the analysis of current status data with a cured proportion in the population using a mixture model that combines a logistic regression formulation for the probability of cure with a semiparametric regression model for the time to occurrence of the event. The semiparametric regression model belongs to the flexible class of partly linear models that allows one to explore the possibly nonlinear effect of a certain covariate on the response variable. A sieve maximum likelihoo...
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作者：Lawless, JF; Fredette, M
作者单位：University of Waterloo; Universite de Montreal; HEC Montreal
摘要：We consider parametric frameworks for the prediction of future values of a random variable Y, based on previously observed data X. Simple pivotal methods for obtaining calibrated prediction intervals are presented and illustrated. Frequentist predictive distributions are defined as confidence distributions, and their utility is demonstrated. A simple pivotal-based approach that produces prediction intervals and predictive distributions with well-calibrated frequentist probability interpretatio...
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作者：Crainiceanu, C; Ruppert, D; Claeskens, G; Wand, MP
作者单位：Johns Hopkins University; Cornell University; KU Leuven; University of New South Wales Sydney
摘要：Penalised-spline-based additive models allow a simple mixed model representation where the variance components control departures from linear models. The smoothing parameter is the ratio of the random-coefficient and error variances and tests for linear regression reduce to tests for zero random-coefficient variances. We propose exact likelihood and restricted likelihood ratio tests for testing polynomial regression versus a general alternative modelled by penalised splines. Their spectral dec...
