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作者：Li, Lexin
作者单位：North Carolina State University
摘要：Existing sufficient dimension reduction methods suffer from the fact that each dimension reduction component is a linear combination of all the original predictors, so that it is difficult to interpret the resulting estimates. We propose a unified estimation strategy, which combines a regression-type formulation of sufficient dimension reduction methods and shrinkage estimation, to produce sparse and accurate solutions. The method can be applied to most existing sufficient dimension reduction ...
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作者：Shao, Yongwu; Cook, R. Dennis; Weisberg, Sanford
作者单位：University of Minnesota System; University of Minnesota Twin Cities
摘要：We present a new computationally feasible test for the dimension of the central subspace in a regression problem based on sliced average variance estimation. We also provide a marginal coordinate test. Under the null hypothesis, both the test of dimension and the marginal coordinate test involve test statistics that asymptotically have chi-squared distributions given normally distributed predictors, and have a distribution that is a linear combination of chi-squared distributions in general.
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作者：Sen, Bodhisattva; Banerjee, Moulinath
作者单位：University of Michigan System; University of Michigan
摘要：We introduce a method based on a pseudolikelihood ratio for estimating the distribution function of the survival time in a mixed-case interval censoring model. In a mixed-case model, an individual is observed a random number of times, and at each time it is recorded whether an event has happened or not. One seeks to estimate the distribution of time to event. We use a Poisson process as the basis of a likelihood function to construct a pseudolikelihood ratio statistic for testing the value of ...
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作者：Thompson, Elizabeth A.; Geyer, Charles J.
作者单位：University of Washington; University of Washington Seattle; University of Minnesota System; University of Minnesota Twin Cities
摘要：We consider the problem of testing a statistical hypothesis where the scientifically meaningful test statistic is a function of latent variables. In particular, we consider detection of genetic linkage, where the latent variables are patterns of inheritance at specific genome locations. Introduced by Geyer & Meeden (2005), fuzzy p-values are random variables, described by their probability distributions, that are interpreted as p-values. For latent variable problems, we introduce the notion of...
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作者：Martinussen, Torben; Scheike, Thomas H.
作者单位：University of Copenhagen; University of Copenhagen
摘要：We study a test comparing the full Aalen additive hazards model and the change-point model, and suggest how to estimate the parameters of the change-point model. We also study a test for no change-point effect. Both tests are provided with large sample properties and a resampling method is applied to obtain p-values. The finite-sample properties of the proposed inference procedures and estimators are assessed through a simulation study. The methods are further applied to a dataset concerning m...
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作者：Fienberg, Stephen E.; Kim, Sung-Ho
作者单位：Carnegie Mellon University; Korea Advanced Institute of Science & Technology (KAIST)
摘要：We show that, when the three-way association level among the three binary variables, X, U-1 and U-2 is fixed, D-P = pr( X = 1 | U-1 = 1) - pr( X = 1 | U-1 = 0) increases as the cross-product ratio of U-1 and U-2 increases under the assumption that X is positively associated with U-1 and U-2. We then discuss some implications of this property.
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作者：Bayarri, M. J.; Garcia-Donato, Gonzalo
作者单位：University of Valencia; Universidad de Castilla-La Mancha
摘要：We consider that observations come from a general normal linear model and that it is desirable to test a simplifying null hypothesis about the parameters. We approach this problem from an objective Bayesian, model-selection perspective. Crucial ingredients for this approach are 'proper objective priors' to be used for deriving the Bayes factors. Jeffreys-Zellner-Siow priors have good properties for testing null hypotheses defined by specific values of the parameters in full-rank linear models....
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作者：Kong, Efang; Xia, Yingcun
作者单位：National University of Singapore
摘要：We consider variable selection in the single-index model. We prove that the popular leave-m-out crossvalidation method has different behaviour in the single-index model from that in linear regression models or nonparametric regression models. A new consistent variable selection method, called separated crossvalidation, is proposed. Further analysis suggests that the method has better finite-sample performance and is computationally easier than leave-m-out crossvalidation. Separated crossvalida...
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作者：Duan, Jason A.; Guindani, Michele; Gelfand, Alan E.
作者单位：Yale University; University of New Mexico; Duke University
摘要：Many models for the study of point-referenced data explicitly introduce spatial random effects to capture residual spatial association. These spatial effects are customarily modelled as a zero-mean stationary Gaussian process. The spatial Dirichlet process introduced by Gelfand et al. (2005) produces a random spatial process which is neither Gaussian nor stationary. Rather, it varies about a process that is assumed to be stationary and Gaussian. The spatial Dirichlet process arises as a probab...
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作者：Geyer, Charles J.; Wagenius, Stuart; Shaw, Ruth G.
作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities
摘要：We present a new class of statistical models, designed for life history analysis of plants and animals, that allow joint analysis of data on survival and reproduction over multiple years, allow for variables having different probability distributions, and correctly account for the dependence of variables on earlier variables. We illustrate their utility with an analysis of data taken from an experimental study of Echinacea angustifolia sampled from remnant prairie populations in western Minnes...
