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作者：Consonni, G; Leucari, V
作者单位：University of Pavia
摘要：The combination of graphical models and reference analysis represents a powerful tool for Bayesian inference in highly multivariate settings. It is typically difficult to derive reference priors in complex problems. In this paper we present a suitable mixed parameterisation for a discrete decomposable graphical model and derive the corresponding reference prior.
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作者：Huang, JZ; Liu, NP; Pourahmadi, M; Liu, LX
作者单位：Texas A&M University System; Texas A&M University College Station; University of Pennsylvania; Northern Illinois University; Columbia University
摘要：We propose a nonparametric method for identifying parsimony and for producing a statistically efficient estimator of a large covariance matrix. We reparameterise a covariance matrix through the modified Cholesky decomposition of its inverse or the one-step-ahead predictive representation of the vector of responses and reduce the nonintuitive task of modelling covariance matrices to the familiar task of model selection and estimation for a sequence of regression models. The Cholesky factor cont...
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作者：Jennison, C; Turnbull, BW
作者单位：University of Bath; Cornell University
摘要：Methods have been proposed for redesigning a clinical trial at an interim stage in order to increase power. In order to preserve the type I error rate, methods for unplanned design-change have to be defined in terms of nonsufficient statistics, and this calls into question their efficiency and the credibility of conclusions reached. We evaluate schemes for adaptive redesign, extending the theoretical arguments for use of sufficient statistics of Tsiatis & Mehta (2003) and assessing the possibl...
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作者：Lin, N; He, XM
作者单位：Washington University (WUSTL); University of Illinois System; University of Illinois Urbana-Champaign
摘要：The minimum Hellinger distance estimator is known to have desirable properties in terms of robustness and efficiency. We propose an approximate minimum Hellinger distance estimator by adapting the approach to grouped data from a continuous distribution. It is easier to compute the approximate version for either the continuous data or the grouped data. Given certain conditions on the model distribution and reasonable grouping rules, the approximate minimum Hellinger distance estimator is shown ...
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作者：Cook, RD; Ni, LQ
作者单位：University of Minnesota System; University of Minnesota Twin Cities; State University System of Florida; University of Central Florida
摘要：Popular methods for estimating the central subspace in regression require slicing a continuous response. However, slicing can result in loss of information and in some cases that loss can be substantial. We use intraslice covariances to construct improved inference methods for the central subspace. These methods are optimal within a class of quadratic inference functions and permit chi-squared tests of conditional independence hypotheses involving the predictors. Our experience gained through ...
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作者：Pintore, A; Speckman, P; Holmes, CC
作者单位：University of Oxford; University of Missouri System; University of Missouri Columbia
摘要：We use a reproducing kernel Hilbert space representation to derive the smoothing spline solution when the smoothness penalty is a function lambda(t) of the design space t, thereby allowing the model to adapt to various degrees of smoothness in the structure of the data. We propose a convenient form for the smoothness penalty function and discuss computational algorithms for automatic curve fitting using a generalised crossvalidation measure.
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作者：Ma, Y; Chiou, JM; Wang, N
作者单位：Texas A&M University System; Texas A&M University College Station; Academia Sinica - Taiwan
摘要：We study the heteroscedastic partially linear model with an unspecified partial baseline component and a nonparametric variance function. An interesting finding is that the performance of a naive weighted version of the existing estimator could deteriorate when the smooth baseline component is badly estimated. To avoid this, we propose a family of consistent estimators and investigate their asymptotic properties. We show that the optimal semiparametric efficiency bound can be reached by a semi...
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作者：Huang, XZ; Stefanski, LA; Davidian, M
作者单位：North Carolina State University
摘要：We present methods for diagnosing the effects of model misspecification of the true-predictor distribution in structural measurement error models. We first formulate latent-model robustness theoretically. Then we provide practical techniques for examining the adequacy of an assumed latent predictor model. The methods are illustrated via analytical examples, application to simulated data and with data from a study of coronary heart disease.
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作者：Lin, CT; Wu, JS; Yen, CH
作者单位：Tamkang University
摘要：Jones (1989) has pointed out that piecewise linear interpolated kernel density estimators on a sufficiently fine grid can be visually indistinguishable from the true density. A simple device, the kernel polygon, is proposed for eliminating the evaluation of the normalisation constant of the estimator while retaining its property of being a density function as well as providing practical advantages. The class of uniform and linear kernels of the kernel polygons is given. Finally, we present a s...
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作者：Chaganty, NR; Joe, H
作者单位：Old Dominion University; University of British Columbia
摘要：We say that a pair (p, R) is compatible if there exists a multivariate binary distribution with mean vector p and correlation matrix R. In this paper we study necessary and sufficient conditions for compatibility for structured and unstructured correlation matrices. We give examples of correlation matrices that are incompatible with any p. Using our results we show that the parametric binary models of Emrich & Piedmonte (1991) and Qaqish (2003) allow a good range of correlations between the bi...
