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作者：PFANZAGL, J
摘要：Let (P(theta,eta):(theta,eta) is-an-element-of THETA x H), with THETA is-an-element-of R and H arbitrary, be a family of mutually absolutely continuous probability measures on a measurable space (X,A). The problem is to estimate theta, based on a sample (x1,...,x(n)) from X1(n)P(theta,etanu). If (eta1,...,eta(n)) are independently distributed according to some unknown prior distribution GAMMA, then the distribution of n1/2(theta(n) - theta) under P(theta,GAMMA)n(P(theta,GAMMA) being the GAMMA-...
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作者：YOHAI, VJ; ZAMAR, RH
作者单位：University of British Columbia
摘要：A natural measure of the degree of robustness of an estimate T is the maximum asymptotic bias B(T)(epsilon) over an epsilon-contamination neighborhood. Martin, Yohai and Zamar have shown that the class of least alpha-quantile regression estimates is minimax bias in the class of M-estimates, that is, they minimize B(T)(epsilon), with a depending on epsilon. In this paper we generalize this result, proving that the least alpha-quantile estimates are minimax bias in a much broader class of estima...
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作者：SASIENI, P
摘要：New estimators for Cox regression are considered. Their asymptotic properties, both on and off the model, are established. Corollaries include conditions under which the maximum partial likelihood estimator defines a parameter in the population and the asymptotics of the case-cohort estimator. Robust estimators that minimize the asymptotic variance subject to a bound on the maximal bias on infinitesimal neighborhoods are discussed. The estimators are illustrated with medical data.
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作者：HUSKOVA, M; JANSSEN, P
作者单位：Hasselt University
摘要：A generalized bootstrap version is defined for degenerate U-statistics. Our main result shows that the (conditional) distribution function of the bootstrapped degenerate U-statistic provides a consistent estimator for the unknown distribution function of the degenerate U-statistic under consideration. For the proof we rely on a rank statistic approach.
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作者：BOOTH, JG; HALL, P
作者单位：Australian National University
摘要：We suggest bootstrap methods for constructing confidence bands (and intervals) for an unknown linear functional relationship in an errors-invariables model. It is assumed that the ratio of error variances is known to lie within an interval LAMBDA = [lambda1, lambda2]. A confidence band is constructed for the range of possible linear relationships when lambda is-an-element-of LAMBDA. Meaningful results are obtained even in the extreme case LAMBDA = [0, infinity], which corresponds to no assumpt...
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作者：DIACONIS, P; FREEDMAN, DA
作者单位：University of California System; University of California Berkeley
摘要：The performance of Bayes estimates are studied, under an assumption of conditional exchangeability. More exactly, for each subject in a data set, let xi be a vector of binary covariates and let eta be a binary response variable, with P{eta = 1\xi} = f(xi). Here, f is an unknown function to be estimated from the data; the subjects are independent, and satisfy a natural ''balance'' condition. Define a prior distribution on f as SIGMA(k)omega(k)pi(k)/SIGMA(k)omega(k), where pi(k) is uniform on th...
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作者：FAN, JQ; TRUONG, YK
作者单位：University of North Carolina; University of North Carolina Chapel Hill
摘要：The effect of errors in variables in nonparametric regression estimation is examined. To account for errors in covariates, deconvolution is involved in the construction of a new class of kernel estimators. It is shown that optimal local and global rates of convergence of these kernel estimators can be characterized by the tail behavior of the characteristic function of the error distribution. In fact, there are two types of rates of convergence according to whether the error is ordinary smooth...
