Biometrika

最新文章

• Survival analysis without survival data: connecting length-biased and case-control data AI翻译
  作者：Chan, Kwun Chuen Gary
  作者单位：University of Washington; University of Washington Seattle
  摘要：We show that relative mean survival parameters of a semiparametric log-linear model can be estimated using covariate data from an incident sample and a prevalent sample, even when there is no prospective follow-up to collect any survival data. Estimation is based on an induced semiparametric density ratio model for covariates from the two samples, and it shares the same structure as for a logistic regression model for case-control data. Likelihood inference coincides with well-established meth...
• The role of the range parameter for estimation and prediction in geostatistics AI翻译
  作者：Kaufman, C. G.; Shaby, B. A.
  作者单位：University of California System; University of California Berkeley
  摘要：Two canonical problems in geostatistics are estimating the parameters in a specified family of stochastic process models and predicting the process at new locations. We show that asymptotic results for a Gaussian process over a fixed domain with Matern covariance function, previously proven only in the case of a fixed range parameter, can be extended to the case of jointly estimating the range and the variance of the process. Moreover, we show that intuition and approximations derived from asy...
• Dimension reduction and predictor selection in semiparametric models AI翻译
  作者：Yu, Zhou; Zhu, Liping; Peng, Heng; Zhu, Lixing
  作者单位：East China Normal University; Shanghai University of Finance & Economics; Hong Kong Baptist University
  摘要：Dimension reduction in semiparametric regressions includes construction of informative linear combinations and selection of contributing predictors. To reduce the predictor dimension in semiparametric regressions, we propose an l(1)-minimization of sliced inverse regression with the Dantzig selector, and establish a non-asymptotic error bound for the resulting estimator. We also generalize the regularization concept to sliced inverse regression with an adaptive Dantzig selector. This ensures t...
• A multiple comparison procedure for hypotheses with gatekeeping structure AI翻译
  作者：Luo, Xiaolong; Chen, Guang; Ouyang, S. Peter; Turnbull, Bruce W.
  作者单位：Bristol-Myers Squibb; Celgene Corporation; Cornell University
  摘要：We develop gatekeeping procedures that focus on comparing multiple treatments with a control when there are multiple endpoints. Our procedures utilize estimated correlations among individual test statistics without parametric assumptions. We make comparisons with other gatekeeping procedures with respect to properties of the trade-off in statistical power between families of hypotheses. We introduce a reward function to facilitate these comparisons. We illustrate our methods by simulation and ...
• Efficient estimation of the censored linear regression model AI翻译
  作者：Lin, Yuanyuan; Chen, Kani
  作者单位：Hong Kong Polytechnic University; Hong Kong University of Science & Technology
  摘要：In linear regression or accelerated failure time models, complications in efficient estimation arise from the multiple roots of the efficient score and density estimation. This paper proposes a one-step efficient estimation method based on a counting process martingale, which has several advantages: it avoids the multiple-root problem, the initial estimator is easily available and the variance estimator can be obtained by employing plug-in rules. A simple and effective data-driven bandwidth se...
• A central limit theorem in the β-model for undirected random graphs with a diverging number of vertices AI翻译
  作者：Yan, Ting; Xu, Jinfeng
  作者单位：Central China Normal University; New York University
  摘要：Chatterjee et al. (2011) established the consistency of the maximum likelihood estimator in the beta-model for undirected random graphs when the number of vertices goes to infinity. By approximating the inverse of the Fisher information matrix, we prove asymptotic normality of the maximum likelihood estimator under mild conditions. Simulation studies and a data example illustrate the theoretical results.
• Efficient Gaussian process regression for large datasets AI翻译
  作者：Banerjee, Anjishnu; Dunson, David B.; Tokdar, Surya T.
  作者单位：Duke University
  摘要：Gaussian processes are widely used in nonparametric regression, classification and spatiotemporal modelling, facilitated in part by a rich literature on their theoretical properties. However, one of their practical limitations is expensive computation, typically on the order of n(3) where n is the number of data points, in performing the necessary matrix inversions. For large datasets, storage and processing also lead to computational bottlenecks, and numerical stability of the estimates and p...
• Covariate-adjusted precision matrix estimation with an application in genetical genomics AI翻译
  作者：Cai, T. Tony; Li, Hongzhe; Liu, Weidong; Xie, Jichun
  作者单位：University of Pennsylvania; University of Pennsylvania; Shanghai Jiao Tong University; Shanghai Jiao Tong University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
  摘要：Motivated by analysis of genetical genomics data, we introduce a sparse high-dimensional multivariate regression model for studying conditional independence relationships among a set of genes adjusting for possible genetic effects. The precision matrix in the model specifies a covariate-adjusted Gaussian graph, which presents the conditional dependence structure of gene expression after the confounding genetic effects on gene expression are taken into account. We present a covariate-adjusted p...
• Saddlepoint approximations for the normalizing constant of Fisher-Bingham distributions on products of spheres and Stiefel manifolds AI翻译
  作者：Kume, A.; Preston, S. P.; Wood, Andrew T. A.
  作者单位：University of Kent; University of Nottingham
  摘要：In an earlier paper Kume & Wood (2005) showed how the normalizing constant of the Fisher-Bingham distribution on a sphere can be approximated with high accuracy using a univariate saddlepoint density approximation. In this sequel, we extend the approach to a more general setting and derive saddlepoint approximations for the normalizing constants of multicomponent Fisher-Bingham distributions on Cartesian products of spheres, and Fisher-Bingham distributions on Stiefel manifolds. In each case, ...
• Smoothing splines with varying smoothing parameter AI翻译
  作者：Wang, Xiao; Du, Pang; Shen, Jinglai
  作者单位：Purdue University System; Purdue University; Virginia Polytechnic Institute & State University; University System of Maryland; University of Maryland Baltimore County
  摘要：This paper considers the development of spatially adaptive smoothing splines for the estimation of a regression function with nonhomogeneous smoothness across the domain. Two challenging issues arising in this context are the evaluation of the equivalent kernel and the determination of a local penalty. The penalty is a function of the design points in order to accommodate local behaviour of the regression function. We show that the spatially adaptive smoothing spline estimator is approximately...