Journal of the Royal Statistical Society: Series B

最新文章

• Spatial spline regression models AI翻译
  作者：Sangalli, Laura M.; Ramsay, James O.; Ramsay, Timothy O.
  作者单位：Polytechnic University of Milan; McGill University; University of Ottawa; Ottawa Hospital Research Institute
  摘要：We describe a model for the analysis of data distributed over irregularly shaped spatial domains with complex boundaries, strong concavities and interior holes. Adopting an approach that is typical of functional data analysis, we propose a spatial spline regression model that is computationally efficient, allows for spatially distributed covariate information and can impose various conditions over the boundaries of the domain. Accurate surface estimation is achieved by the use of piecewise lin...
• Inference for linear models with dependent errors AI翻译
  作者：Zhou, Zhou; Shao, Xiaofeng
  作者单位：University of Toronto; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：. The paper is concerned with inference for linear models with fixed regressors and weakly dependent stationary time series errors. Theoretically, we obtain asymptotic normality for the M-estimator of the regression parameter under mild conditions and establish a uniform Bahadur representation for recursive M-estimators. Methodologically, we extend the recently proposed self-normalized approach of Shao from stationary time series to the regression set-up, where the sequence of response variabl...
• Estimating heterogeneity variance in meta-analysis AI翻译
  作者：Rukhin, Andrew L.
  作者单位：National Institute of Standards & Technology (NIST) - USA
  摘要：. Several new estimators of the between-study variability in a heterogeneous random effects meta-analysis model are derived. One is the unbiased statistic which is locally optimal for small values of the parameter. Others are Bayes procedures within a class of quadratic statistics for a diffuse prior with different choices of the prior mean. These estimators are compared with the DerSimonianLaird procedure and the Hedges statistic in particular via the quadratic risk of the treatment effect es...
• Robust estimation for homoscedastic regression in the secondary analysis of case-control data AI翻译
  作者：Wei, Jiawei; Carroll, Raymond J.; Mueller, Ursula U.; Van Keilegom, Ingrid; Chatterjee, Nilanjan
  作者单位：Texas A&M University System; Texas A&M University College Station; Universite Catholique Louvain; Tilburg University; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI)
  摘要：Primary analysis of case-control studies focuses on the relationship between disease D and a set of covariates of interest (Y, X). A secondary application of the case-control study, which is often invoked in modern genetic epidemiologic association studies, is to investigate the interrelationship between the covariates themselves. The task is complicated owing to the case-control sampling, where the regression of Y on X is different from what it is in the population. Previous work has assumed ...
• Doubly robust and efficient estimators for heteroscedastic partially linear single-index models allowing high dimensional covariates AI翻译
  作者：Ma, Yanyuan; Zhu, Liping
  作者单位：Texas A&M University System; Texas A&M University College Station; Shanghai University of Finance & Economics
  摘要：. We study the heteroscedastic partially linear single-index model with an unspecified error variance function, which allows for high dimensional covariates in both the linear and the single-index components of the mean function. We propose a class of consistent estimators of the parameters by using a proper weighting strategy. An interesting finding is that the linearity condition which is widely assumed in the dimension reduction literature is not necessary for methodological or theoretical ...
• Optimal predictions of powers of conditionally heteroscedastic processes AI翻译
  作者：Francq, Christian; Zakoian, Jean-Michel
  作者单位：Institut Polytechnique de Paris; ENSAE Paris; Universite de Lille
  摘要：. In conditionally heteroscedastic models, the optimal prediction of powers, or logarithms, of the absolute value has a simple expression in terms of the volatility and an expectation involving the independent process. A natural procedure for estimating this prediction is to estimate the volatility in the first step, for instance by Gaussian quasi-maximum-likelihood or by least absolute deviations, and to use empirical means based on rescaled innovations to estimate the expectation in the seco...
• New local estimation procedure for a non-parametric regression function for longitudinal data AI翻译
  作者：Yao, Weixin; Li, Runze
  作者单位：Kansas State University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
  摘要：The paper develops a new estimation of non-parametric regression functions for clustered or longitudinal data. We propose to use Cholesky decomposition and profile least squares techniques to estimate the correlation structure and regression function simultaneously. We further prove that the estimator proposed is as asymptotically efficient as if the covariance matrix were known. A Monte Carlo simulation study is conducted to examine the finite sample performance of the procedure proposed, and...
• Point process modelling for directed interaction networks AI翻译
  作者：Perry, Patrick O.; Wolfe, Patrick J.
  作者单位：New York University; University of London; University College London
  摘要：Network data often take the form of repeated interactions between senders and receivers tabulated over time. A primary question to ask of such data is which traits and behaviours are predictive of interaction. To answer this question, a model is introduced for treating directed interactions as a multivariate point process: a Cox multiplicative intensity model using covariates that depend on the history of the process. Consistency and asymptotic normality are proved for the resulting partial-li...
• Marginal log-linear parameters for graphical Markov models AI翻译
  作者：Evans, Robin J.; Richardson, Thomas S.
  作者单位：University of Cambridge; University of Washington; University of Washington Seattle
  摘要：Marginal log-linear (MLL) models provide a flexible approach to multivariate discrete data. MLL parameterizations under linear constraints induce a wide variety of models, including models that are defined by conditional independences. We introduce a subclass of MLL models which correspond to acyclic directed mixed graphs under the usual global Markov property. We characterize for precisely which graphs the resulting parameterization is variation independent. The MLL approach provides the firs...
• Condition-number-regularized covariance estimation AI翻译
  作者：Won, Joong-Ho; Lim, Johan; Kim, Seung-Jean; Rajaratnam, Bala
  作者单位：Korea University; Seoul National University (SNU); Stanford University
  摘要：Estimation of high dimensional covariance matrices is known to be a difficult problem, has many applications and is of current interest to the larger statistics community. In many applications including the so-called large p, small n' setting, the estimate of the covariance matrix is required to be not only invertible but also well conditioned. Although many regularization schemes attempt to do this, none of them address the ill conditioning problem directly. We propose a maximum likelihood ap...