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作者：He, Yi; Einmahl, John H. J.
作者单位：Tilburg University; Tilburg University
摘要：Consider the extreme quantile region induced by the half-space depth function HD of the form Q={xRd:HD(x,P)}, such that PQ=p for a given, very small p>0. Since this involves extrapolation outside the data cloud, this region can hardly be estimated through a fully non-parametric procedure. Using extreme value theory we construct a natural semiparametric estimator of this quantile region and prove a refined consistency result. A simulation study clearly demonstrates the good performance of our e...
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作者：Wong, Raymond K. W.; Storlie, Curtis B.; Lee, Thomas C. M.
作者单位：Iowa State University; United States Department of Energy (DOE); Los Alamos National Laboratory; University of California System; University of California Davis
摘要：The paper considers the computer model calibration problem and provides a general frequentist solution. Under the framework proposed, the data model is semiparametric with a non-parametric discrepancy function which accounts for any discrepancy between physical reality and the computer model. In an attempt to solve a fundamentally important (but often ignored) identifiability issue between the computer model parameters and the discrepancy function, the paper proposes a new and identifiable par...
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作者：Kennedy, Edward H.; Ma, Zongming; McHugh, Matthew D.; Small, Dylan S.
作者单位：University of Pennsylvania
摘要：Continuous treatments (e.g. doses) arise often in practice, but many available causal effect estimators are limited by either requiring parametric models for the effect curve, or by not allowing doubly robust covariate adjustment. We develop a novel kernel smoothing approach that requires only mild smoothness assumptions on the effect curve and still allows for misspecification of either the treatment density or outcome regression. We derive asymptotic properties and give a procedure for data-...
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作者：Gao, Jiti; Han, Xiao; Pan, Guangming; Yang, Yanrong
作者单位：Monash University; Nanyang Technological University
摘要：Statistical inferences for sample correlation matrices are important in high dimensional data analysis. Motivated by this, the paper establishes a new central limit theorem for a linear spectral statistic of high dimensional sample correlation matrices for the case where the dimension p and the sample size n are comparable. This result is of independent interest in large dimensional random-matrix theory. We also further investigate the sample correlation matrices of a high dimensional vector w...
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作者：Dunson, David; Fryzlewicz, Piotr
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作者：Fan, Caiyun; Lu, Wenbin; Song, Rui; Zhou, Yong
作者单位：Shanghai University of International Business & Economics; North Carolina State University; Shanghai University of Finance & Economics; Chinese Academy of Sciences
摘要：We propose new concordance-assisted learning for estimating optimal individualized treatment regimes. We first introduce a type of concordance function for prescribing treatment and propose a robust rank regression method for estimating the concordance function. We then find treatment regimes, up to a threshold, to maximize the concordance function, named the prescriptive index. Finally, within the class of treatment regimes that maximize the concordance function, we find the optimal threshold...
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作者：Gromenko, Oleksandr; Kokoszka, Piotr; Reimherr, Matthew
作者单位：Tulane University; Colorado State University System; Colorado State University Fort Collins; Pennsylvania Commonwealth System of Higher Education (PCSHE); Pennsylvania State University; Pennsylvania State University - University Park
摘要：The paper develops inferential methodology for detecting a change in the annual pattern of an environmental variable measured at fixed locations in a spatial region. Using a framework built on functional data analysis, we model observations as a collection of function-valued time sequences available at many sites. Each sequence is modelled as an annual mean function, which may change, plus a sequence of error functions, which are spatially correlated. The tests statistics extend the cumulative...
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作者：Rukhin, Andrew L.
作者单位：National Institute of Standards & Technology (NIST) - USA
摘要：To determine the common mean of heterogeneous normal observations, the Bayes procedures and the invariant maximum likelihood estimators of the weights forming the weighted means statistic are obtained when there are no variance estimates. The Bayes statistic is based on the reference, Geisser-Cornfield prior distribution which makes the posterior (discrete) distribution of the mean to be supported by the observed data with probabilities determined via the geometric means of the distances betwe...
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作者：Barber, Rina Foygel; Ramdas, Aaditya
作者单位：University of Chicago; University of California System; University of California Berkeley
摘要：In many practical applications of multiple testing, there are natural ways to partition the hypotheses into groups by using the structural, spatial or temporal relatedness of the hypotheses, and this prior knowledge is not used in the classical Benjamini-Hochberg procedure for controlling the false discovery rate (FDR). When one can define (possibly several) such partitions, it may be desirable to control the group FDR simultaneously for all partitions (as special cases, the 'finest' partition...
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作者：Shao, Qin; Yang, Lijian
作者单位：Soochow University - China; University System of Ohio; University of Toledo; Tsinghua University
摘要：Most time series that are encountered in practice contain non-zero trend, yet textbook approaches to time series analysis are typically focused on zero-mean stationary auto-regressive moving average (ARMA) processes. Trend is often estimated by ad hoc methods and subtracted from time series, and the residuals are used as the true ARMA noise for data analysis and inference, including parameter estimation, lag selection and prediction. We propose a theoretically justified two-step method to anal...
