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作者：Li, Bing; Dong, Yuexiao
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：Sufficient dimension reduction methods often require stringent conditions on the joint distribution of the predictor, or, when such conditions are not satisfied, rely on marginal transformation or reweighting to fulfill them approximately. For example, a typical dimension reduction method would require the predictor to have elliptical or even multivariate normal distribution. In this paper, we reformulate the commonly used dimension reduction methods, via the notion of central solution space, ...
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作者：Jongbloed, Geurt; van der Meulen, Frank H.
作者单位：Delft University of Technology
摘要：We consider two nonparametric procedures for estimating a concave distribution function based on data corrupted with additive noise generated by a bounded decreasing density on (0, infinity). For the maximum likelihood (ML) estimator and least squares (LS) estimator, we state qualitative properties, prove consistency and propose a computational algorithm. For the LS estimator and its derivative, we also derive the pointwise asymptotic distribution. Moreover, the rate n(-2/5) achieved by the LS...
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作者：Sun, Yanqing; Gilbert, Peter B.; McKeague, Ian W.
作者单位：University of North Carolina; University of North Carolina Charlotte; University of Washington; University of Washington Seattle; Fred Hutchinson Cancer Center; Columbia University
摘要：For time-to-event data with finitely many competing risks, the proportional hazards model has been a popular tool for relating the cause-specific outcomes to covariates [Prentice et al. Biometrics 34 (1978) 541-554]. This article studies an extension of this approach to allow a continuum of competing risks, in which the cause of failure is replaced by a continuous mark only observed at the failure time. We develop inference for the proportional hazards model in which the regression parameters ...
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作者：Andersson, Sofia; Ryden, Tobias
作者单位：AstraZeneca; Lund University
摘要：Hidden Markov models (HMMs) are probabilistic functions of finite Markov chains, or, put in other words, state space models with finite state space. In this paper, we examine subspace estimation methods for HMMs whose output lies a finite set as well. In particular, we study the geometric structure arising from the nonminimality of the linear state space representation of HMMs, and consistency of a subspace algorithm arising from a certain factorization of the singular value decomposition of t...
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作者：Ranjan, Pritam; Bingham, Derek R.; Dean, Angela M.
作者单位：Acadia University; Simon Fraser University; University System of Ohio; Ohio State University
摘要：Regular factorial designs with randomization restrictions are widely used in practice. This paper provides a unified approach to the construction of such designs using randomization defining contrast subspaces for the representation of randomization restrictions. We use finite projective geometry to determine the existence of designs with the required structure and develop a systematic approach for their construction. An attractive feature is that commonly used factorial designs with randomiza...
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作者：Fukumizu, Kenji; Bach, Francis R.; Jordan, Michael I.
作者单位：Research Organization of Information & Systems (ROIS); Institute of Statistical Mathematics (ISM) - Japan; Inria; Universite PSL; Ecole Normale Superieure (ENS); Centre National de la Recherche Scientifique (CNRS); CNRS - Institute for Information Sciences & Technologies (INS2I); University of California System; University of California Berkeley
摘要：We present a new methodology for sufficient dimension reduction (SDR). Our methodology derives directly from the formulation of SDR in terms of the conditional independence of the covariate X from the response Y, given the projection of X on the central subspace [cf. J. Amer Statist. Assoc. 86 (1991) 316-342 and Regression Graphics (1998) Wiley]. We show that this conditional independence assertion can be characterized in terms of conditional covariance operators on reproducing kernel Hilbert ...
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作者：Finner, Helmut; Dickhaus, Thorsten; Roters, Markus
作者单位：Leibniz Association; Deutsches Diabetes-Zentrum (DDZ)
摘要：In this paper we introduce and investigate a new rejection curve for asymptotic control of the false discovery rate (FDR) in multiple hypotheses testing problems. We first give a heuristic motivation for this new curve and propose some procedures related to it. Then we introduce a set of possible assumptions and give a unifying short proof of FDR control for procedures based on Simes' critical values, whereby certain types of dependency are allowed. This methodology of proof is then applied to...
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作者：Muler, Nora; Pena, Daniel; Yohai, Victor J.
作者单位：Universidad Carlos III de Madrid
摘要：This paper introduces a new class of robust estimates for ARMA models. They are M-estimates, but the residuals are computed so the effect of one outlier is limited to the period where it occurs. These estimates are closely related to those based on a robust filter, but they have two important advantages: they are consistent and the asymptotic theory is tractable. We perform a Monte Carlo where we show that these estimates compare favorably with respect to standard M-estimates and to estimates ...
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作者：Nguyen, XuanLong; Wainwright, Martin J.; Jordan, Michael I.
作者单位：Duke University; University of California System; University of California Berkeley; University of California System; University of California Berkeley
摘要：The goal of binary classification is to estimate a discriminant function gamma from observations of covariate vectors and corresponding binary labels. We consider an elaboration of this problem in which the covariates are not available directly but are transformed by a dimensionality-reducing quantizer Q. We present conditions on loss functions such that empirical risk minimization yields Bayes consistency when both the discriminant function and the quantizer are estimated. These conditions ar...
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作者：Dette, Holger; Holland-Letz, Tim
作者单位：Ruhr University Bochum; Ruhr University Bochum
摘要：We consider the common nonlinear regression model where the variance, as well as the mean, is a parametric function of the explanatory variables. The c-optimal design problem is investigated in the case when the parameters of both the mean and the variance function are of interest. A geometric characterization of c-optimal designs in this context is presented, which generalizes the classical result of Elfving [Ann. Math. Statist. 23 (1952) 255-262] for c-optimal designs. As in Elfving's famous...
