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作者：Sanderson, J.; Fryzlewicz, P.; Jones, M. W.
作者单位：University of Bristol; University of London; London School Economics & Political Science; University of Bristol
摘要：Large volumes of neuroscience data comprise multiple, nonstationary electrophysiological or neuroimaging time series recorded from different brain regions. Accurately estimating the dependence between such neural time series is critical, since changes in the dependence structure are presumed to reflect functional interactions between neuronal populations. We propose a new dependence measure, derived from a bivariate locally stationary wavelet time series model. Since wavelets are localized in ...
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作者：Fearnhead, Paul; Wyncoll, David; Tawn, Jonathan
作者单位：Lancaster University
摘要：In this paper we propose a new particle smoother that has a computational complexity of O(N), where N is the number of particles. This compares favourably with the O(N-2) computational cost of most smoothers. The new method also overcomes some degeneracy problems in existing algorithms. Through simulation studies we show that substantial gains in efficiency are obtained for practical amounts of computational cost. It is shown both through these simulation studies, and by the analysis of an ath...
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作者：Wang, Xiao; Shen, Jinglai
作者单位：Purdue University System; Purdue University; University System of Maryland; University of Maryland Baltimore County
摘要：We study a class of monotone univariate regression estimators. We use B-splines to approximate an underlying regression function and estimate spline coefficients based on grouped data. We investigate asymptotic properties of two monotone estimators: a grouped Brunk estimator and a penalized monotone estimator. These estimators are consistent at the boundary and their mean square errors achieve optimal convergence rates under suitable assumptions of the true regression function. Asymptotic dist...
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作者：Tan, Zhiqiang
作者单位：Rutgers University System; Rutgers University New Brunswick
摘要：Consider estimating the mean of an outcome in the presence of missing data or estimating population average treatment effects in causal inference. A doubly robust estimator remains consistent if an outcome regression model or a propensity score model is correctly specified. We build on a previous nonparametric likelihood approach and propose new doubly robust estimators, which have desirable properties in efficiency if the propensity score model is correctly specified, and in boundedness even ...
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作者：Lee, A. J.; Scott, A. J.; Wild, C. J.
作者单位：University of Auckland
摘要：In this paper we discuss the analysis of multi-phase, or multi-stage, case-control studies and present an efficient semiparametric maximum-likelihood approach that unifies and extends earlier work, including the seminal case-control paper by Prentice & Pyke (1979), work by Breslow & Cain (1988), Scott & Wild (1991), Breslow & Holubkov (1997) and others. The theoretical derivations apply to arbitrary binary regression models but we present results for logistic regression and show that the appro...
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作者：Wu, Samuel S.; Wang, Weizhen; Yang, Mark C. K.
作者单位：State University System of Florida; University of Florida; University System of Ohio; Wright State University Dayton; State University System of Florida; University of Florida
摘要：In the first stage of a two-stage, drop-the-losers design, a candidate for the best treatment is selected. At the second stage, additional observations are collected to decide whether the candidate is actually better than the control. The design also allows the investigator to stop the trial for ethical reasons at the end of the first stage if there is already strong evidence of futility or superiority. Two types of tests have recently been developed, one based on the combined means and the ot...
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作者：Dette, H.; Kiss, C.; Bevanda, M.; Bretz, Frank
作者单位：Ruhr University Bochum; Novartis
摘要：We derive locally D- and EDp-optimal designs for the exponential, log-linear and three-parameter emax models. For each model the locally D- and EDp-optimal designs are supported at the same set of points, while the corresponding weights are different. This indicates that for a given model, D-optimal designs are efficient for estimating the smallest dose that achieves 100p% of the maximum effect in the observed dose range. Conversely, EDp-optimal designs also yield good D-efficiencies. We illus...
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作者：Dong, Yuexiao; Li, Bing
作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); Temple University; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：Many classical dimension reduction methods, especially those based on inverse conditional moments, require the predictors to have elliptical distributions, or at least to satisfy a linearity condition. Such conditions, however, are too strong for some applications. Li and Dong (2009) introduced the notion of the central solution space and used it to modify first-order methods, such as sliced inverse regression, so that they no longer rely on these conditions. In this paper we generalize this i...
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作者：Wang, Junhui
作者单位：University of Illinois System; University of Illinois Chicago; University of Illinois Chicago Hospital
摘要：In cluster analysis, one of the major challenges is to estimate the number of clusters. Most existing approaches attempt to minimize some distance-based dissimilarity measure within clusters. This article proposes a novel selection criterion that is applicable to all kinds of clustering algorithms, including distance based or non-distance based algorithms. The key idea is to select the number of clusters that minimizes the algorithm's instability, which measures the robustness of any given clu...
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作者：Cox, D. R.; Wong, M. Y.
作者单位：University of Oxford; Hong Kong University of Science & Technology
摘要：A simple case of Poisson regression is used to study the potential gain in efficiency from using a mixed model representation. Possible systematic errors arising from misspecification of the random terms in the model are examined. It is shown in particular that for a special but realistic problem, appreciable bias may arise from misspecification of a random component.
