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作者：Arnold, R.; Jupp, P. E.
作者单位：Victoria University Wellington; University of St Andrews
摘要：An orthogonal axial frame is a set of orthonormal unit vectors which are known only up to sign. Such frames arise in crystallography and seismology and as principal axes of multivariate data or of some physical tensors. We develop methods for analysing data of this form. A test of uniformity is given. Parametric models for orthogonal axial frames are presented and tests of location are considered. A brief illustrative example involving earthquakes is given.
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作者：McCaffrey, Daniel F.; Lockwood, J. R.; Setodji, Claude M.
作者单位：RAND Corporation
摘要：Inverse probability-weighted estimators are widely used in applications where data are missing due to nonresponse or censoring and in the estimation of causal effects from observational studies. Current estimators rely on ignorability assumptions for response indicators or treatment assignment and outcomes being conditional on observed covariates which are assumed to be measured without error. However, measurement error is common for the variables collected in many applications. For example, i...
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作者：Lin, Feng-Chang; Cai, Jianwen; Fine, Jason P.; Lai, Huichuan J.
作者单位：University of North Carolina; University of North Carolina Chapel Hill; University of Wisconsin System; University of Wisconsin Madison
摘要：Recurrent event data frequently arise in longitudinal studies when study subjects possibly experience more than one event during the observation period. Often, such recurrent events can be categorized. However, part of the categorization may be missing due to technical difficulties. If the event types are missing completely at random, then a complete case analysis may provide consistent estimates of regression parameters in certain regression models, but estimates of the baseline event rates a...
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作者：Zhang, Baqun; Tsiatis, Anastasios A.; Laber, Eric B.; Davidian, Marie
作者单位：Renmin University of China; North Carolina State University
摘要：A dynamic treatment regime is a list of sequential decision rules for assigning treatment based on a patient's history. Q- and A-learning are two main approaches for estimating the optimal regime, i.e., that yielding the most beneficial outcome in the patient population, using data from a clinical trial or observational study. Q-learning requires postulated regression models for the outcome, while A-learning involves models for that part of the outcome regression representing treatment contras...
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作者：Ning, Yang; Liu, Han
作者单位：University of Waterloo; Princeton University
摘要：In multivariate analysis, a Gaussian bigraphical model is commonly used for modelling matrix-valued data. In this paper, we propose a semiparametric extension of the Gaussian bigraphical model, called the nonparanormal bigraphical model. A projected nonparametric rank-based regularization approach is employed to estimate sparse precision matrices and produce graphs under a penalized likelihood framework. Theoretically, our semiparametric procedure achieves the parametric rates of convergence f...
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作者：Chan, Kwun Chuen Gary
作者单位：University of Washington; University of Washington Seattle
摘要：We show that relative mean survival parameters of a semiparametric log-linear model can be estimated using covariate data from an incident sample and a prevalent sample, even when there is no prospective follow-up to collect any survival data. Estimation is based on an induced semiparametric density ratio model for covariates from the two samples, and it shares the same structure as for a logistic regression model for case-control data. Likelihood inference coincides with well-established meth...
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作者：Yu, Zhou; Zhu, Liping; Peng, Heng; Zhu, Lixing
作者单位：East China Normal University; Shanghai University of Finance & Economics; Hong Kong Baptist University
摘要：Dimension reduction in semiparametric regressions includes construction of informative linear combinations and selection of contributing predictors. To reduce the predictor dimension in semiparametric regressions, we propose an l(1)-minimization of sliced inverse regression with the Dantzig selector, and establish a non-asymptotic error bound for the resulting estimator. We also generalize the regularization concept to sliced inverse regression with an adaptive Dantzig selector. This ensures t...
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作者：Beaumont, J. -F.; Haziza, D.; Ruiz-Gazen, A.
作者单位：Statistics Canada; Universite de Montreal; Universite de Toulouse; Universite Toulouse 1 Capitole; Toulouse School of Economics
摘要：We argue that the conditional bias associated with a sample unit can be a useful measure of influence in finite population sampling. We use the conditional bias to derive robust estimators that are obtained by downweighting the most influential sample units. Under the model-based approach to inference, our proposed robust estimator is closely related to the well-known estimator of Chambers (1986). Under the design-based approach, it possesses the desirable feature of being applicable with most...
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作者：Bissiri, P. G.; Ongaro, A.; Walker, S. G.
作者单位：University of Milano-Bicocca; University of Kent
摘要：This paper considers species sampling models using constructions that arise from Bayesian nonparametric prior distributions. A discrete random measure, used to generate a species sampling model, can have either a countable infinite number of atoms, which has been the emphasis in the recent literature, or a finite number of atoms K, while allowing K to be assigned a prior probability distribution on the positive integers. It is the latter class of model we consider here, due to the interpretati...
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作者：Mueller, Hans-Georg; Wu, Yichao; Yao, Fang
作者单位：University of California System; University of California Davis; North Carolina State University; University of Toronto
摘要：We introduce continuously additive models, which can be viewed as extensions of additive regression models with vector predictors to the case of infinite-dimensional predictors. This approach produces a class of flexible functional nonlinear regression models, where random predictor curves are coupled with scalar responses. In continuously additive modelling, integrals taken over a smooth surface along graphs of predictor functions relate the predictors to the responses in a nonlinear fashion....
