6期

最新文章

• Spline-backfitted kernel smoothing of nonlinear additive autoregression model AI翻译
  作者：Wang, Li; Yang, Lijian
  作者单位：University System of Georgia; University of Georgia; Michigan State University
  摘要：Application of nonparametric and semiparametric regression techniques to high-dimensional time series data has been hampered due to the lack of effective tools to address the curse of dimensionality. Under rather weak conditions, we propose spline-backfitted kernel estimators of the component functions for the nonlinear additive time series data that are both computationally expedient so they are usable for analyzing very high-dimensional time series, and theoretically reliable so inference ca...
• Discussion:: The Dantzig selector:: Statistical estimation when p is much larger than n AI翻译
  作者：Efron, Bradley; Hastie, Trevor; Tibshiran, Robert
  作者单位：Stanford University
• Stepup procedures controlling generalized FWER and generalized FDR AI翻译
  作者：Sarkar, Sanat K.
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University
  摘要：In many applications of multiple hypothesis testing where more than one false rejection can be tolerated, procedures controlling error rates measuring at least k false rejections, instead of at least one, for some fixed k >= 1 can potentially increase the ability of a procedure to detect false null hypotheses. The k-FWER, a generalized version of the usual familywise error rate (FWER), is such an error rate that has recently been introduced in the literature and procedures controlling it have ...
• Consistency of cross validation for comparing regression procedures AI翻译
  作者：Yang, Yuhong
  作者单位：University of Minnesota System; University of Minnesota Twin Cities
  摘要：Theoretical developments on cross validation (CV) have mainly focused on selecting one among a list of finite-dimensional models (e.g., subset or order selection in linear regression) or selecting a smoothing parameter (e.g., bandwidth for kernel smoothing). However, little is known about consistency of cross validation when applied to compare between parametric and nonparametric methods or within nonparametric methods. We show that under some conditions, with an appropriate choice of data spl...
• Discussion:: The Dantzig selector:: Statistical estimation when p is much larger than n AI翻译
  作者：Cai, T. Tony; Lv, Jinchi
  作者单位：University of Pennsylvania; Princeton University
• Analysis of boosting algorithms using the smooth margin function AI翻译
  作者：Rudin, Cynthia; Schapire, Robert E.; Daubechies, Ingrid
  作者单位：Columbia University; Princeton University; Princeton University
  摘要：We introduce a useful tool for analyzing boosting algorithms called the smooth margin function, a differentiable approximation of the usual margin for boosting algorithms. We present two boosting algorithms based on this smooth margin, coordinate ascent boosting and approximate coordinate ascent boosting, which are similar to Freund and Schapire's AdaBoost algorithm and Breiman's arc-gv algorithm. We give convergence rates to the maximum margin solution for both of our algorithms and for arc-g...
• Discussion:: The Dantzig selector:: Statistical estimation when p is much larger than n AI翻译
  作者：Bickel, Peter J.
  作者单位：University of California System; University of California Berkeley
• Discussion: A tale of three cousins: Lasso, L2Boosting and Dantzig AI翻译
  作者：Meinshausen, N.; Rocha, G.; Yu, B.
  作者单位：University of Oxford; University of California System; University of California Berkeley
• Estimation of the covariance matrix of random effects in longitudinal studies AI翻译
  作者：Sun, Yan; Zhang, Wenyang; Tong, Howell
  作者单位：Shanghai University of Finance & Economics; University of Kent; University of London; London School Economics & Political Science
  摘要：Longitudinal studies are often conducted to explore the cohort and age effects in many scientific areas. The within cluster correlation structure plays a very important role in longitudinal data analysis. This is because not only can an estimator be improved by incorporating the within cluster correlation structure into the estimation procedure, but also the within cluster correlation structure can sometimes provide valuable insights in practical problems. For example, it can reveal the correl...
• A constructive approach to the estimation of dimension reduction directions AI翻译
  作者：Xia, Yingcun
  作者单位：National University of Singapore
  摘要：In this paper we propose two new methods to estimate the dimension-reduction directions of the central subspace (CS) by constructing a regression model such that the directions are all captured in the regression mean. Compared with the inverse regression estimation methods [e.g., J. Amer Statist. Assoc. 86 (1991) 328-332, J Amer Statist. Assoc. 86 (1991) 316-342, J Amer Statist. Assoc. 87 (1992) 1025-1039], the new methods require no strong assumptions on the design of covariates or the functi...