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作者：Zeng, Donglin; Gao, Fei; Lin, D. Y.
作者单位：University of North Carolina; University of North Carolina Chapel Hill
摘要：Interval-censored multivariate failure time data arise when there are multiple types of failure or there is clustering of study subjects and each failure time is known only to lie in a certain interval. We investigate the effects of possibly time-dependent covariates on multivariate failure times by considering a broad class of semiparametric transformation models with random effects, and we study nonparametric maximum likelihood estimation under general interval-censoring schemes. We show tha...
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作者：Dalal, Onkar; Rajaratnam, Bala
作者单位：Stanford University; University of California System; University of California Davis
摘要：Several methods have recently been proposed for estimating sparse Gaussian graphical models using l(1)-regularization on the inverse covariance or precision matrix. Despite recent advances, contemporary applications require even faster methods to handle ill-conditioned high-dimensional datasets. In this paper, we propose a new method for solving the sparse inverse covariance estimation problem using the alternating minimization algorithm, which effectively works as a proximal gradient algorith...
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作者：Ehm, W.; Ovcharov, E. Y.
作者单位：Heidelberg Institute for Theoretical Studies; Bulgarian Academy of Sciences
摘要：Decompositions of the score of a forecast represent useful tools for assessing its performance. We consider local score decompositions permitting detailed forecast assessments across a spectrum of conditions of interest. We derive corrections to the bias of the decomposition components in the framework of point forecasts of quantile-type functionals, and illustrate their performance by simulation. Related bias corrections have thus far only been known for squared error criteria.
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作者：Lam, Clifford; Feng, Phoenix; Hu, Charlie
作者单位：University of London; London School Economics & Political Science
摘要：Integrated covariance matrices arise in intraday models of asset returns, which allow volatility to change over the trading day. When the number of assets is large, the natural estimator of such a matrix suffers from bias due to extreme eigenvalues. We introduce a novel nonlinear shrinkage estimator for the integrated covariance matrix which shrinks the extreme eigenvalues of a realized covariance matrix back to an acceptable level, and enjoys a certain asymptotic efficiency when the number of...
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作者：She, Y.; Chen, K.
作者单位：State University System of Florida; Florida State University; University of Connecticut
摘要：In high-dimensional multivariate regression problems, enforcing low rank in the coefficient matrix offers effective dimension reduction, which greatly facilitates parameter estimation and model interpretation. However, commonly used reduced-rank methods are sensitive to data corruption, as the low-rank dependence structure between response variables and predictors is easily distorted by outliers. We propose a robust reduced-rank regression approach for joint modelling and outlier detection. Th...
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作者：Sun, Fasheng; Tang, Boxin
作者单位：Northeast Normal University - China; Simon Fraser University
摘要：Orthogonal Latin hypercubes provide a class of useful designs for computer experiments. Among the available methods for constructing such designs, the method of rotation is particularly prominent due to its theoretical appeal as well as its space-filling properties. This paper presents a general method of rotation for constructing orthogonal Latin hypercubes, making the rotation idea applicable to many more situations than the original method allows. In addition to general theoretical results,...
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作者：Sadinle, Mauricio; Reiter, Jerome P.
作者单位：Duke University
摘要：We introduce a nonresponse mechanism for multivariate missing data in which each study variable and its nonresponse indicator are conditionally independent given the remaining variables and their nonresponse indicators. This is a nonignorable missingness mechanism, in that nonresponse for any item can depend on values of other items that are themselves missing. We show that under this itemwise conditionally independent nonresponse assumption, one can define and identify nonparametric saturated...
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作者：Dobler, D.; Beyersmann, J.; Pauly, M.
作者单位：Ulm University
摘要：This paper introduces a new data-dependent multiplier bootstrap for nonparametric analysis of survival data, possibly subject to competing risks. The new procedure includes the general wild bootstrap and the weird bootstrap as special cases. The data may be subject to independent right-censoring and left-truncation. The asymptotic correctness of the proposed resampling procedure is proven under standard assumptions. Simulation results on time-simultaneous inference suggest that the weird boots...
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作者：Fattorini, L.; Marcheselli, M.; Pisani, C.; Pratelli, L.
作者单位：University of Siena
摘要：We analyse design-based properties of two-phase strategies for estimating totals and nonlinear functions of totals for environmental populations when the sampling schemes are uniquely determined by points placed in the study region. In the first phase, points are located using tessellation stratified sampling, whereas in the second phase a finite population sampling scheme is adopted. We give sufficient conditions on second-phase designs that ensure consistency, and we investigate the variance...
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作者：He, Xu
作者单位：Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS
摘要：We propose a new method for constructing minimax distance designs, which are useful for computer experiments. To circumvent computational difficulties, we consider designs with an interleaved lattice structure, a newly defined class of lattice that has repeated or alternated layers based on any single dimension. Such designs have boundary adaptation and low-thickness properties. From our numerical results, the proposed designs are by far the best minimax distance designs for moderate or large ...
