Biometrika

最新文章

• Testing the covariance structure of multivariate random fields AI翻译
  作者：Li, Bo; Genton, Marc G.; Sherman, Michael
  作者单位：Purdue University System; Purdue University; Texas A&M University System; Texas A&M University College Station
  摘要：There is an increasing wealth of multivariate spatial and multivariate spatio-temporal data appearing. For such data, an important part of model building is an assessment of the properties of the underlying covariance function describing variable, spatial and temporal correlations. In this paper, we propose a methodology to evaluate the appropriateness of several types of common assumptions on multivariate covariance functions in the spatio-temporal context. The methodology is based on the asy...
• A multi-dimensional scaling approach to shape analysis AI翻译
  作者：Dryden, Ian L.; Kume, Alfred; Le, Huiling; Wood, Andrew T. A.
  作者单位：University of Nottingham; University of Kent
  摘要：We propose an alternative to Kendall's shape space for reflection shapes of configurations in Rm with k labelled vertices, where reflection shape consists of all the geometric information that is invariant under compositions of similarity and reflection transformations. The proposed approach embeds the space of such shapes into the space P( k - 1) of ( k - 1) x ( k - 1) real symmetric positive semidefinite matrices, which is the closure of an open subset of a Euclidean space, and defines mean ...
• Bayesian nonparametric inference on stochastic ordering AI翻译
  作者：Dunson, David B.; Peddada, Shyamal D.
  作者单位：Duke University; National Institutes of Health (NIH) - USA; NIH National Institute of Environmental Health Sciences (NIEHS)
  摘要：We consider Bayesian inference about collections of unknown distributions subject to a partial stochastic ordering. To address problems in testing of equalities between groups and estimation of group-specific distributions, we propose classes of restricted dependent Dirichlet process priors. These priors have full support in the space of stochastically ordered distributions, and can be used for collections of unknown mixture distributions to obtain a flexible class of mixture models. Theoretic...
• On the asymptotics of penalized splines AI翻译
  作者：Li, Yingxing; Ruppert, David
  作者单位：Cornell University; Cornell University
  摘要：We study the asymptotic behaviour of penalized spline estimators in the univariate case. We use B-splines and a penalty is placed on mth-order differences of the coefficients. The number of knots is assumed to converge to infinity as the sample size increases. We show that penalized splines behave similarly to Nadaraya - Watson kernel estimators with 'equivalent' kernels depending upon m. The equivalent kernels we obtain for penalized splines are the same as those found by Silverman for smooth...
• Nonparametric regression using local kernel estimating equations for correlated failure time data AI翻译
  作者：Yu, Zhangsheng; Lin, Xihong
  作者单位：University System of Ohio; Ohio State University; Harvard University; Harvard T.H. Chan School of Public Health
  摘要：We study nonparametric regression for correlated failure time data. Kernel estimating equations are used to estimate nonparametric covariate effects. Independent and weighted-kernel estimating equations are studied. The derivative of the nonparametric function is first estimated and the nonparametric function is then estimated by integrating the derivative estimator. We show that the nonparametric kernel estimator is consistent for any arbitrary working correlation matrix and that its asymptot...
• Forecasting with the age-period-cohort model and the extended chain-ladder model AI翻译
  作者：Kuang, D.; Nielsen, B.; Nielsen, J. P.
  作者单位：University of Oxford; University of Oxford; City St Georges, University of London
  摘要：We consider forecasting from age-period-cohort models, as well as from the extended chain-ladder model. The parameters of these models are known only to be identified up to linear trends. Forecasts from such models may therefore depend on arbitrary linear trends. A condition for invariant forecasts is proposed. A number of standard forecast models are analysed.
• Influence functions and robust Bayes and empirical Bayes small area estimation AI翻译
  作者：Ghosh, Malay; Maiti, Tapabrata; Roy, Ananya
  作者单位：State University System of Florida; University of Florida; Iowa State University; University of Nebraska System; University of Nebraska Lincoln
  摘要：We introduce new robust small area estimation procedures based on area-level models. We first find influence functions corresponding to each individual area-level observation by measuring the divergence between the posterior density functions of regression coefficients with and without that observation. Next, based on these influence functions, properly standardized, we propose some new robust Bayes and empirical Bayes small area estimators. The mean squared errors and estimated mean squared e...
• Conditionally specified continuous distributions AI翻译
  作者：Wang, Yuchung J.; Ip, Edward H.
  作者单位：Rutgers University System; Rutgers University New Brunswick; Rutgers University Camden; Wake Forest University; Wake Forest Baptist Medical Center
  摘要：A distribution is conditionally specified when its model constraints are expressed conditionally. For example, Besag's (1974) spatial model was specified conditioned on the neighbouring states, and pseudolikelihood is intended to approximate the likelihood using conditional likelihoods. There are three issues of interest: existence, uniqueness and computation of a joint distribution. In the literature, most results and proofs are for discrete probabilities; here we exclusively study distributi...
• Predicting cumulative incidence probability by direct binomial regression AI翻译
  作者：Scheike, Thomas H.; Zhang, Mei-Jie; Gerds, Thomas A.
  作者单位：University of Copenhagen; Medical College of Wisconsin; University of Freiburg
  摘要：We suggest a new simple approach for estimation and assessment of covariate effects for the cumulative incidence curve in the competing risks model. We consider a semiparametric regression model where some effects may be time-varying and some may be constant over time. Our estimator can be implemented by standard software. Our simulation study shows that the estimator works well and has finite-sample properties comparable with the subdistribution approach. We apply the method to bone marrow tr...
• Probability estimation for large-margin classifiers AI翻译
  作者：Wang, Junhui; Shen, Xiaotong; Liu, Yufeng
  作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of North Carolina; University of North Carolina Chapel Hill
  摘要：Large margin classifiers have proven to be effective in delivering high predictive accuracy, particularly those focusing on the decision boundaries and bypassing the requirement of estimating the class probability given input for discrimination. As a result, these classifiers may not directly yield an estimated class probability, which is of interest itself. To overcome this difficulty, this article proposes a novel method for estimating the class probability through sequential classifications...