-
作者：Ramdas, Aaditya; Chen, Jianbo; Wainwright, Martin J.; Jordan, Michael I.
作者单位：Carnegie Mellon University; University of California System; University of California Berkeley
摘要：We propose a linear-time, single-pass, top-down algorithm for multiple testing on directed acyclic graphs, where nodes represent hypotheses and edges specify a partial ordering in which the hypotheses must be tested. The procedure is guaranteed to reject a sub-directed acyclic graph with bounded false discovery rate while satisfying the logical constraint that a rejected node's parents must also be rejected. It is designed for sequential testing settings where the directed acyclic graph struct...
-
作者：Yuan, Yiping; Shen, Xiaotong; Pan, Wei; Wang, Zizhuo
作者单位：University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities; University of Minnesota System; University of Minnesota Twin Cities
摘要：Directed acyclic graphs are widely used to describe directional pairwise relations. Such relations are estimated by reconstructing a directed acyclic graph's structure, which is challenging when the ordering of nodes of the graph is unknown. In such a situation, existing methods such as the neighbourhood and search-and-score methods have high estimation errors or computational complexities, especially when a local or sequential approach is used to enumerate edge directions by testing or optimi...
-
作者：Johndrow, J. E.; Lum, K.; Manrique-Vallier, D.
作者单位：Stanford University; Indiana University System; Indiana University Bloomington
摘要：Population estimation methods are used for estimating the size of a population from samples of individuals. In many applications, the probability of being observed in the sample varies across individuals, resulting in sampling bias. We show that in this setting, estimators of the population size have high and sometimes infinite risk, leading to large uncertainty in the population size. As an alternative, we propose estimating the population of individuals with observation probability exceeding...
-
作者：Rosenblatt, Jonathan D.; Ritov, Ya'acov; Goeman, Jelle J.
作者单位：Ben-Gurion University of the Negev; University of Michigan System; University of Michigan; Leiden University; Leiden University Medical Center (LUMC); Leiden University - Excl LUMC
-
作者：Sesia, M.; Sabatti, C.; Candes, E. J.
作者单位：Stanford University
-
作者：Descary, M. -H.; Panaretos, V. M.
作者单位：University of Quebec; University of Quebec Montreal; Swiss Federal Institutes of Technology Domain; Ecole Polytechnique Federale de Lausanne
摘要：We consider nonparametric estimation of a covariance function on the unit square, given a sample of discretely observed fragments of functional data. When each sample path is observed only on a subinterval of length , one has no statistical information on the unknown covariance outside a -band around the diagonal. The problem seems unidentifiable without parametric assumptions, but we show that nonparametric estimation is feasible under suitable smoothness and rank conditions on the unknown co...
-
作者：Jewell, S. W.; Witten, D. M.
作者单位：University of Washington; University of Washington Seattle; University of Washington; University of Washington Seattle
-
作者：Sun, Qiang; Zhu, Ruoqing; Wang, Tao; Zeng, Donglin
作者单位：University of Toronto; University of Illinois System; University of Illinois Urbana-Champaign; Shanghai Jiao Tong University; University of North Carolina; University of North Carolina Chapel Hill
摘要：We propose counting process-based dimension reduction methods for right-censored survival data. Semiparametric estimating equations are constructed to estimate the dimension reduction subspace for the failure time model. Our methods address two limitations of existing approaches. First, using the counting process formulation, they do not require estimation of the censoring distribution to compensate for the bias in estimating the dimension reduction subspace. Second, the nonparametric estimati...
