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作者：Robinson, Peter M.; Zaffaroni, Paolo
作者单位：University of London; London School Economics & Political Science; Imperial College London
摘要：Strong consistency and asymptotic normality of the Gaussian pseudomaximum likelihood estimate of the parameters in a wide class of ARCH(infinity) processes are established. The conditions are shown to hold in case of exponential and hyperbolic decay in the ARCH weights, though in the latter case a faster decay rate is required for the central limit theorem than for the law of large numbers. Particular parameterizations are discussed.
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作者：Zhu, Hongtu; Zhang, Heping
作者单位：Columbia University; New York State Psychiatry Institute; Yale University; Jiangxi Normal University
摘要：Many important problems in psychology and biomedical studies require testing for overdispersion, correlation and heterogeneity in mixed effects and latent variable models, and score tests are particularly useful for this purpose. But the existing testing procedures depend on restrictive assumptions. In this paper we propose a class of test statistics based on a general mixed effects model to test the homogeneity hypothesis that all of the variance components are zero. Under some mild condition...
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作者：Marinucci, Domenico
作者单位：University of Rome Tor Vergata
摘要：In this paper we study the asymptotic behavior of the angular bispectrum of spherical random fields. Here, the asymptotic theory is developed in the framework of fixed-radius fields, which are observed with increasing resolution as the sample size grows. The results we present are then exploited in a set of procedures aimed at testing non-Gaussianity; for these statistics, we are able to show convergence to functionals of standard Brownian motion under the null hypothesis. Analytic results are...
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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
