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作者：EINMAHL, JHJ; MASON, DM
作者单位：University of Delaware
摘要：For random vectors taking values in R(d) we introduce a notion of multivariate quantiles defined in terms of a class of sets and study an associated process which we call the generalized quantile process. This process specializes to the well known univariate quantile process. We obtain functional central limit theorems for our generalized quantile process and show that both Gaussian and non-Gaussian limiting processes can arise. A number of interesting example are included.
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作者：ARCONES, MA; GINE, E
作者单位：University of Connecticut; City University of New York (CUNY) System
摘要：Bootstrap distributional limit theorems for U and V statistics are proved. They hold a.s., under weak moment conditions and without restrictions on the bootstrap sample size (as long as it tends to infinity), regardless of the degree of degeneracy of U and V. A testing procedure based on these results is outlined.
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作者：HOLLANDER, M; PRESNELL, B; SETHURAMAN, J
作者单位：State University System of Florida; University of Florida
摘要：In the age-dependent minimal repair model of Block, Borges and Savits (BBS), a system failing at age t undergoes one of two types of repair. With probability p(t), a perfect repair is performed and the system is returned to the good-as-new state, while with probability 1 - p(t), a minimal repair is performed and the system is repaired, but is only as good as a working system of age t. Whitaker and Samaniego propose an estimator for the system life distribution F when data are collected under t...
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作者：SZKUTNIK, Z
作者单位：AGH University of Krakow
摘要：The problem of maximin testing between families of probability measures generated by special capacities and transformation groups is solved by showing that the Hunt-Stein theorem is applicable to such, generally nondominated, families of probability measures and that the problem reduces to maximin testing between neighbourhoods of distributions of maximal invariant, defined by special capacities closely related to the initial ones. An application to testing approximate binormality is also sket...
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作者：ZHOU, M
摘要：This article studies the large sample behavior of the censored data least squares estimator derived from the synthetic data method proposed by Leurgans and Zheng. The asymptotic distributions are derived by representing the estimator as a martingale plus a higher-order remainder term. Recently developed counting process techniques are used. The results are then compared to the censored regression estimator of Koul, Susarla and Van Ryzin.
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作者：HALL, P
摘要：It is argued that mean integrated squared error is not a useful measure of the performance of a variable bandwidth density estimator based on Abramson's square root law. The reason is that when the unknown density f has even moderately light tails, properties of those tails drive the formula for optimal bandwidth, to the virtual exclusion of other properties of f. We suggest that weighted integrated squared error be employed as the performance criterion, using a weight function with compact su...
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作者：KO, DJ
摘要：We introduce a simple procedure for obtaining robust estimates of the concentration parameter of the von Mises-Fisher distribution on the q-dimensional unit sphere. The procedure is based on the median deviation from a location parameter. Its influence function is derived and standardized bias robustness is proved. The asymptotic efficiency is calculated and an example is given.
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作者：RUBIN, DB; THOMAS, N
作者单位：Educational Testing Service (ETS)
摘要：Matched sampling is a common technique used for controlling bias in observational studies. We present a general theoretical framework for studying the performance of such matching methods. Specifically, results are obtained concerning the performance of affinely invariant matching methods with ellipsoidal distributions, which extend previous results on equal percent bias reducing methods. Additional extensions cover conditionally affinely invariant matching methods for covariates with conditio...
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作者：MARRON, JS; WAND, MP
作者单位：Rice University
摘要：An exact and easily computable expression for the mean integrated squared error (MISE) for the kernel estimator of a general normal mixture density, is given for Gaussian kernels of arbitrary order. This provides a powerful new way of understanding density estimation which complements the usual tools of simulation and asymptotic analysis. The family of normal mixture densities is very flexible and the formulae derived allow simple exact analysis for a wide variety of density shapes. A number o...
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作者：HALL, P
摘要：The bootstrap is a poor estimator of bias in problems of curve estimation, and so bias must be corrected by other means when the bootstrap is used to construct confidence intervals for a probability density. Bias may either be estimated explicitly, or allowed for by undersmoothing the curve estimator. Which of these two approaches is to be preferred? In the present paper we address this question from the viewpoint of coverage accuracy, assuming a given number of derivatives of the unknown dens...
