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作者：Chen, Aiyou; Bickel, Peter J.
作者单位：Alcatel-Lucent; Lucent Technologies; AT&T; University of California System; University of California Berkeley
摘要：Independent component analysis (ICA) has been widely used for blind source separation in many fields, such as brain imaging analysis, signal processing and telecommunication. Many statistical techniques based on M-estimates have been proposed for estimating the mixing matrix. Recently, several nonparametric methods have been developed, but in-depth analysis of asymptotic efficiency has not been available. We analyze ICA using semiparametric theories and propose a straightforward estimate based...
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作者：Meinshausen, Nicolai; Buehlmann, Peter
作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
摘要：The pattern of zero entries in the inverse covariance matrix of a multivariate normal distribution corresponds to conditional independence restrictions between variables. Covariance selection aims at estimating those structural zeros from data. We show that neighborhood selection with the Lasso is a computationally attractive alternative to standard covariance selection for sparse high-dimensional graphs. Neighborhood selection estimates the conditional independence restrictions separately for...
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作者：Bickel, Peter J.; Ritov, Ya'acov; Stoker, Thomas M.
作者单位：University of California System; University of California Berkeley; Hebrew University of Jerusalem; Massachusetts Institute of Technology (MIT)
摘要：We introduce a new framework for constructing tests of general semiparametric hypotheses which have nontrivial power on the n(-1/2) scale in every direction, and can be tailored to put substantial power on alternatives of importance. The approach is based on combining test statistics based on stochastic processes of score statistics with bootstrap critical values.
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作者：George, Edward I.; Liang, Feng; Xu, Xinyi
作者单位：University of Pennsylvania; Duke University; University System of Ohio; Ohio State University
摘要：Let X vertical bar mu similar to N-p(mu, v(x)I) and Y vertical bar mu - Np(mu, v(y)l) be independent p-dimensional multivariate normal vectors with common unknown mean mu. Based on only observing X = x, we consider the problem of obtaining a predictive density (p) over cap (y vertical bar x) for Y that is close to p(y vertical bar mu) as measured by expected Kullback-Leibler loss. A natural procedure for this problem is the (formal) Bayes predictive density (p) over cap (U)(y vertical bar x) u...
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作者：Sweeting, Trevor J.; Datta, Gauri S.; Ghosh, Malay
作者单位：University of London; University College London; University System of Georgia; University of Georgia; State University System of Florida; University of Florida
摘要：We explore the construction of nonsubjective prior distributions in Bayesian statistics via a posterior predictive relative entropy regret criterion. We carry out a minimax analysis based on a derived asymptotic predictive loss function and show that this approach to prior construction has a number of attractive features. The approach here differs from previous work that uses either prior or posterior relative entropy regret in that we consider predictive performance in relation to alternative...
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作者：Lin, Yi; Zhang, Hao Helen
作者单位：University of Wisconsin System; University of Wisconsin Madison; North Carolina State University
摘要：We propose a new method for model selection and model fitting in multivariate nonparametric regression models, in the framework of smoothing spline ANOVA. The COSSO is a method of regularization with the penalty functional being the sum of component norms, instead of the squared norm employed in the traditional smoothing spline method. The COSSO provides a unified framework for several recent proposals for model selection in linear models and smoothing spline ANOVA models. Theoretical properti...
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作者：Thompson, Mary Lou
作者单位：University of Washington; University of Washington Seattle
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作者：Xu, Hongquan
作者单位：University of California System; University of California Los Angeles
摘要：This paper considers the construction of minimum aberration (MA) blocked factorial designs. Based on coding theory, the concept of minimum moment aberration due to Xu [Statist. Sinica 13 (2003) 691-708] for unblocked designs is extended to blocked designs. The coding theory approach studies designs in a row-wise fashion and therefore links blocked designs with nonregular and supersaturated designs. A lower bound on blocked wordlength pattern is established. It is shown that a blocked design ha...
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作者：Bordes, Laurent; Mottelet, Stephane; Vandekerkhove, Pierre
作者单位：Universite de Technologie de Compiegne; Universite Gustave-Eiffel
摘要：Suppose that univariate data are drawn from a mixture of two distributions that are equal up to a shift parameter. Such a model is known to be nonidentifiable from a nonparametric viewpoint. However, if we assume that the unknown mixed distribution is symmetric, we obtain the identifiability of this model, which is then defined by four unknown parameters: the mixing proportion, two location parameters and the cumulative distribution function of the symmetric mixed distribution. We propose esti...
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作者：Leeb, Hannes; Poetscher, Benedikt M.
作者单位：Yale University; University of Vienna
摘要：We consider the problem of estimating the conditional distribution of a post-model-selection estimator where the conditioning is on the selected model. The notion of a post-model-selection estimator here refers to the combined procedure resulting from first selecting a model (e.g., by a model selection criterion such as AIC or by a hypothesis testing procedure) and then estimating the parameters in the selected model (e.g., by least-squares or maximum likelihood), all based on the same data se...
