2期

最新文章

• Product-limit estimators of the survival function with twice censored data AI翻译
  作者：Patilea, Valentin; Rolin, Jean-Marie
  作者单位：Ecole Nationale de la Statistique et de l'Analyse de l'Information (ENSAI); Universite Catholique Louvain
  摘要：A model for competing (resp. complementary) risks survival data where the failure time can be left (resp. right) censored is proposed. Product-limit estimators for the survival functions of the individual risks are derived. We deduce the strong convergence of our estimators on the whole real half-line without any additional assumptions and their asymptotic normality under conditions concerning only the observed distribution. When the observations are generated according to the double censoring...
• Boosting for high-dimensional linear models AI翻译
  作者：Buhlmann, Peter
  作者单位：Swiss Federal Institutes of Technology Domain; ETH Zurich
  摘要：We prove that boosting with the squared error loss, L(2)Boosting, is consistent for very high-dimensional linear models, where the number of predictor variables is allowed to grow essentially as fast as O(exp(sample size)), assuming that the true underlying regression function is sparse in terms of the l(1)-norm of the regression coefficients. In the language of signal processing, this means consistency for de-noising using a strongly overcomplete dictionary if the underlying signal is sparse ...
• Strong invariance principles for sequential Bahadur-Kiefer and Vervaat error processes of long-range dependent sequences AI翻译
  作者：Csorgo, Miklos; Szyszkowicz, Barbara; Wang, Lihong
  作者单位：Carleton University; Nanjing University
  摘要：In this paper we study strong approximations (invariance principles) of the sequential uniform and general Bahadur-Kiefer processes of long-range dependent sequences. We also investigate the strong and weak asymptotic behavior of the sequential Vervaat process, that is, the integrated sequential Bahadur-Kiefer process, properly normalized, as well as that of its deviation from its limiting process, the so-called Vervaat error process. It is well known that the Bahadur-Kiefer and the Vervaat er...
• Fitting an error distribution in some heteroscedastic time series models AI翻译
  作者：Koul, Hira L.; Ling, Shiqing
  作者单位：Michigan State University; Hong Kong University of Science & Technology
  摘要：This paper addresses the problem of fitting a known distribution to the innovation distribution in a class of stationary and ergodic time series models. The asymptotic null distribution of the usual Kolmogorov-Smimov test based on the residuals generally depends on the underlying model parameters and the error distribution. To overcome the dependence on the underlying model parameters, we propose that tests be based on a vector of certain weighted residual empirical processes. Under the null h...
• Adapting to unknown sparsity by controlling the false discovery rate AI翻译
  作者：Abramovich, Felix; Benjamini, Yoav; Donoho, David L.; Johnstone, Iain M.
  作者单位：Tel Aviv University; Stanford University
  摘要：We attempt to recover an n-dimensional vector observed in white noise, where n is large and the vector is known to be sparse, but the degree of sparsity is unknown. We consider three different ways of defining sparsity of a vector: using the fraction of nonzero terms; imposing power-law decay bounds on the ordered entries; and controlling the l(p) norm for p small. We obtain a procedure which is asymptotically minimax for l(r) loss, simultaneously throughout a range of such sparsity classes. T...
• Asymptotic theory for the Cox model with missing time-dependent covariate AI翻译
  作者：Dupuy, Jean-Francois; Grama, Ion; Mesbah, Mounir
  作者单位：Universite de Toulouse; Universite Toulouse III - Paul Sabatier; Sorbonne Universite
  摘要：The relationship between a time-dependent covariate and survival times is usually evaluated via the Cox model. Time-dependent covariates are generally available as longitudinal data collected regularly during the course of the study. A frequent problem, however, is the occurence of missing covariate data. A recent approach to estimation in the Cox model in this case jointly models survival and the longitudinal covariate. However, theoretical justification of this approach is still lacking. In ...
• Characterizing Markov equivalence classes for AMP chain graph models AI翻译
  作者：Andersson, Steen A.; Perlman, Michael D.
  作者单位：Indiana University System; Indiana University Bloomington; University of Washington; University of Washington Seattle
  摘要：Chain graphs (CG) (= adicyclic graphs) use undirected and directed edges to represent both structural and associative dependences. Like acyclic directed graphs (ADGs), the CG associated with a statistical Markov model may not be unique, so CG(S) fall into Markov equivalence classes, which may be superexponentially large, leading to unidentifiability and computational inefficiency in model search and selection. It is shown here that, under the Andersson-Madigan-Perlman (AMP) interpretation of a...
• An iterative procedure for general probability measures to obtain I-projections onto intersections of convex sets AI翻译
  作者：Bhattacharya, Bhaskar
  作者单位：Southern Illinois University System; Southern Illinois University
  摘要：The iterative proportional fitting procedure (IPFP) was introduced formally by Deming and Stephan in 1940. For bivariate densities, this procedure has been investigated by Kullback and Ruschendorf. It is well known that the IPFP is a sequence of successive I-projections onto sets of probability measures with fixed marginals. However, when finding the I-projection onto the intersection of arbitrary closed, convex sets (e.g., marginal stochastic orders), a sequence of successive I-projections on...