Journal of the Royal Statistical Society: Series B

最新文章

• Generalized linear models incorporating population level information: an empirical-likelihood-based approach AI翻译
  作者：Chaudhuri, Sanjay; Handcock, Mark S.; Rendall, Michael S.
  作者单位：National University of Singapore; University of Washington; University of Washington Seattle; RAND Corporation
  摘要：In many situations information from a sample of individuals can be supplemented by population level information on the relationship between a dependent variable and explanatory variables. Inclusion of the population level information can reduce bias and increase the efficiency of the parameter estimates. Population level information can be incorporated via constraints on functions of the model parameters. In general the constraints are non-linear, making the task of maximum likelihood estimati...
• Optimal additions to and deletions from two-level orthogonal arrays AI翻译
  作者：Butler, Neil A.; Ramos, Victorino M.
  作者单位：University of Nottingham; Colegio de Postgraduados - Mexico
  摘要：Consider the problem of selecting a two-level factorial design. It is well known that two-level orthogonal arrays of strength 4 or more with e extra runs have various optimality properties including generalized Cheng (type 1) optimality when e=1, restricted Cheng (type 1) optimality when e=2 and E-optimality when 3 <= e <= 5. More general Schur optimality results are derived for more general values of e within the more restricted class of augmented two-level orthogonal arrays. Similar results ...
• Mixture cure survival models with dependent censoring AI翻译
  作者：Li, Yi; Tiwari, Ram C.; Guha, Subharup
  作者单位：Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; National Institutes of Health (NIH) - USA; NIH National Cancer Institute (NCI)
  摘要：The paper is motivated by cure detection among the prostate cancer patients in the National Institutes of Health surveillance epidemiology and end results programme, wherein the main end point (e.g. deaths from prostate cancer) and the censoring causes (e.g. deaths from heart diseases) may be dependent. Although many researchers have studied the mixture survival model to analyse survival data with non-negligible cure fractions, none has studied the mixture cure model in the presence of depende...
• Coefficient sign prediction methods for model selection AI翻译
  作者：Nott, David J.; Kuk, Anthony Y. C.
  作者单位：National University of Singapore
  摘要：We consider a Bayesian model selection strategy based on predicting the signs of the coefficients in a regression model, i.e. we consider identification of coefficients in a full or encompassing model for which we can confidently predict whether they are positive or negative. This is useful when our main purpose in doing model selection is interpretation, since the sign of a coefficient is often of primary importance for this task. In the case of a linear model with standard non-informative pr...
• On fast computation of the non-parametric maximum likelihood estimate of a mixing distribution AI翻译
  作者：Wang, Yong
  作者单位：University of Auckland
  摘要：A fast algorithm for computing the non-parametric maximum likelihood estimate of a mixing distribution is presented. At each iteration, the algorithm adds new important points to the support set as guided by the gradient function, updates all mixing proportions via a quadratically convergent method and discards redundant support points straightaway. With its convergence being theoretically established, numerical studies show that it is very fast and stable, compared with several other algorith...
• An optimal experimental design criterion for discriminating between non-normal models AI翻译
  作者：Lopez-Fidalgo, J.; Tommasi, C.; Trandafir, P. C.
  作者单位：Universidad de Castilla-La Mancha; University of Milan; University of Salamanca
  摘要：Typically T-optimality is used to obtain optimal designs to discriminate between homoscedastic models with normally distributed observations. Some extensions of this criterion have been made for the heteroscedastic case and binary response models in the literature. In this paper, a new criterion based on the Kullback-Leibler distance is proposed to discriminate between rival models with non-normally distributed observations. The criterion is coherent with the approaches mentioned above. An equ...
• Continuous time modelling of dynamical spatial lattice data observed at sparsely distributed times AI翻译
  作者：Rasmussen, Jakob G.; Moller, Jesper; Aukema, Brian H.; Raffa, Kenneth F.; Zhu, Jun
  作者单位：Aalborg University; Natural Resources Canada; Canadian Forest Service; University of Northern British Columbia; University of Wisconsin System; University of Wisconsin Madison
  摘要：We consider statistical and computational aspects of simulation-based Bayesian inference for a spatial-temporal model based on a multivariate point process which is only observed at sparsely distributed times. The point processes are indexed by the sites of a spatial lattice, and they exhibit spatial interaction. For specificity we consider a particular dynamical spatial lattice data set which has previously been analysed by a discrete time model involving unknown normalizing constants. We dis...
• Maximum likelihood estimation in semiparametric regression models with censored data - Discussion on the paper by Zeng and Lin AI翻译
  作者：Henderson, Robin
  作者单位：University of Newcastle; University of Oslo; Universite de Bordeaux; University of Copenhagen; Hong Kong University of Science & Technology; Columbia University; University of Michigan System; University of Michigan; University of Oxford; Imperial College London; University of Warwick; University of California System; University of California Berkeley; University of Washington; University of Washington Seattle; Open University - UK; Institut National de la Sante et de la Recherche Medicale (Inserm); University of Wisconsin System; University of Wisconsin Madison; Northwestern University; National University of Singapore; University of North Carolina; University of North Carolina Chapel Hill; Seoul National University (SNU); Harvard University; Harvard T.H. Chan School of Public Health; Harvard University; Harvard University Medical Affiliates; Dana-Farber Cancer Institute; Pompeu Fabra University; Umea University; Uppsala University; Fred Hutchinson Cancer Center; University of Greenwich; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne; University of London; Queen Mary University London; Brunel University; Guangxi Normal University; heSam Universite; Conservatoire National Arts & Metiers (CNAM)
• On the non-negative garrotte estimator AI翻译
  作者：Yuan, Ming; Lin, Yi
  作者单位：University System of Georgia; Georgia Institute of Technology; University of Wisconsin System; University of Wisconsin Madison
  摘要：We study the non-negative garrotte estimator from three different aspects: consistency, computation and flexibility. We argue that the non-negative garrotte is a general procedure that can be used in combination with estimators other than the original least squares estimator as in its original form. In particular, we consider using the lasso, the elastic net and ridge regression along with ordinary least squares as the initial estimate in the non-negative garrotte. We prove that the non-negati...
• Statistical inference for evolving periodic functions AI翻译
  作者：Genton, Marc G.; Hall, Peter
  作者单位：Texas A&M University System; Texas A&M University College Station; University of Geneva; Australian National University
  摘要：In the study of variable stars, where the light reaching an observer fluctuates over time, it can be difficult to explain the nature of the variation unless it follows a regular pattern. In this respect, so-called periodic variable stars are particularly amenable to analysis. There, radiation varies in a perfectly periodic fashion, and period length is a major focus of interest. We develop methods for conducting inference about features that might account for departures from strict periodicity...