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作者：Fan, Jianqing; Li, Quefeng; Wang, Yuyan
作者单位：Princeton University; Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; University of North Carolina; University of North Carolina Chapel Hill; Princeton University
摘要：Data subject to heavy-tailed errors are commonly encountered in various scientific fields. To address this problem, procedures based on quantile regression and least absolute deviation regression have been developed in recent years. These methods essentially estimate the conditional median (or quantile) function. They can be very different from the conditional mean functions, especially when distributions are asymmetric and heteroscedastic. How can we efficiently estimate the mean regression f...
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作者：Ji, Hao; Mueller, Hans-Georg
作者单位：University of California System; University of California Davis
摘要：We propose novel optimal designs for longitudinal data for the common situation where the resources for longitudinal data collection are limited, by determining the optimal locations in time where measurements should be taken. As for all optimal designs, some prior information is needed to implement the optimal designs proposed. We demonstrate that this prior information may come from a pilot longitudinal study that has irregularly measured and noisy measurements, where for each subject one ha...
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作者：Jiang, Runchao; Lu, Wenbin; Song, Rui; Davidian, Marie
作者单位：North Carolina State University
摘要：A treatment regime is a deterministic function that dictates personalized treatment based on patients' individual prognostic information. There is increasing interest in finding optimal treatment regimes, which determine treatment at one or more treatment decision points to maximize expected long-term clinical outcomes, where larger outcomes are preferred. For chronic diseases such as cancer or human immunodeficiency virus infection, survival time is often the outcome of interest, and the goal...
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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...
