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作者：CHANG, IS; HSIUNG, CA
作者单位：Academia Sinica - Taiwan
摘要：Proportional hazards models with stochastic baseline hazards and estimators of the relative risk coefficient in these models were proposed by Prentice, Williams and Peterson and by Chang and Hsiung in medical and industrial contexts. The form of the estimating functions recommended varies according to the form of the unknown stochastic baseline hazards. This paper examines the same estimation problem in the context of large-sample theory. It is shown that the proposed estimators are regular, a...
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作者：HUANG, YP; ZHANG, CH
作者单位：Rutgers University System; Rutgers University New Brunswick
摘要：We study the nonparametric maximum likelihood estimator (NPMLE) for a concave distribution function F and its decreasing density f based on right-censored data. Without the concavity constraint, the NPMLE of F is the product-limit estimator proposed by Kaplan and Meier. If there is no censoring, the NPMLE of f, derived by Grenander, is the left derivative of the least concave majorant of the empirical distribution function, and its local and global behavior was investigated, respectively, by P...
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作者：JING, BY; ROBINSON, J
摘要：The Lugannani and Rice formula for tail areas in the univariate case has recently been extended to tail areas for marginal distributions and for conditional distributions in certain multivariate settings. However, the results on relative order of errors are given only formally or under the strong continuity assumptions necessary to obtain density approximations. This paper attempts to give a unified treatment of these results for smooth transformations of multivariate means under weaker condit...
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作者：FYGENSON, M; RITOV, Y
作者单位：Hebrew University of Jerusalem
摘要：The monotone class rank-test-based estimating equations for regression models with right censored data is considered. We introduce an estimator which is a solution of a monotone estimating equation that is an extension of the Gehan test. The estimator is easy to derive, root n-consistent and asymptotically normal under minimal conditions. All monotone estimating equations are characterized, and a simulation study, which shows that our suggested procedure performs well, is included.
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作者：JOHNSTONE, IM
摘要：Mallows has conjectured that among distributions which are Gaussian but for occasional contamination by additive noise, the one having least Fisher information has (two-sided) geometric contamination. A very similar problem arises in estimation of a nonnegative vector parameter in Gaussian white noise when it is known also that most [i.e., (1 - epsilon)) components are zero. We provide a partial asymptotic expansion of the minimax risk as epsilon --> 0. While the conjecture seems unlikely to b...
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作者：KUBOKAWA, T
摘要：In the point and interval estimation of the variance of a normal distribution with an unknown mean, the best affine equivariant estimators are dominated by Stein's truncated and Brewster and Zidek's smooth procedures, which are separately derived. This paper gives a unified approach to this problem by using a simple definite integral and provides a class of improved procedures in both point and interval estimation of powers of the scale parameter of normal, lognormal, exponential and Pareto di...
