1991

最新文章

• LARGE SAMPLE THEORY OF ESTIMATION IN BIASED SAMPLING REGRESSION-MODELS .1. AI翻译
  作者：BICKEL, PJ; RITOV, J
  作者单位：Hebrew University of Jerusalem; Nokia Corporation; Nokia Bell Labs; AT&T; New York University
  摘要：Biased sampling regression models were introduced by Jewell, generalizing the truncated regression model studied by Bhattacharya, Chernoff and Yang. If the independent variable takes on only a finite number of values (as does the stratum variable), we show: 1. That if the slope of the underlying regression model is assumed known, then the nonparametric maximum likelihood estimates of the distribution of the independent and dependent variables (a) can be calculated from ordinary M estimates; (b...
• BAHADUR REPRESENTATIONS FOR UNIFORM RESAMPLING AND IMPORTANCE RESAMPLING, WITH APPLICATIONS TO ASYMPTOTIC RELATIVE EFFICIENCY AI翻译
  作者：HALL, P
  摘要：We derive Bahadur-type representations for quantile estimates obtained from two different types of nonparametric bootstrap resampling-the commonly used uniform resampling method, where each sample value is drawn with the same probability, and importance resampling, where different sample values are assigned different resampling weights. These results are applied to obtain the relative efficiency of uniform resampling and importance resampling and to derive exact convergence rates, both weakly ...
• NONPARAMETRIC REGRESSION UNDER QUALITATIVE SMOOTHNESS ASSUMPTIONS AI翻译
  作者：MAMMEN, E
  摘要：We propose a new nonparametric regression estimate. In contrast to the traditional approach of considering regression functions whose m th derivatives lie in a ball in the L-infinity or L2 norm, we consider the class of functions whose (m - 1)st derivative consists of at most k monotone pieces. For many applications this class seems more natural than the classical ones. The least squares estimator of this class is studied. It is shown that the speed of convergence is as fast as in the classica...
• ESTIMATING A DISTRIBUTION FUNCTION WITH TRUNCATED AND CENSORED-DATA AI翻译
  作者：LAI, TL; YING, ZL
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign
  摘要：A minor modification of the product-limit estimator is proposed for estimating a distribution function (not necessarily continuous) when the data are subject to either truncation or censoring, or to both, by independent but not necessarily identically distributed truncation-censoring variables. Making use of martingale integral representations and empirical process theory, uniform strong consistency of the estimator is established and weak convergence results are proved for the entire observab...
• BAYESIAN PREDICTION IN LINEAR-MODELS - APPLICATIONS TO SMALL AREA ESTIMATION AI翻译
  作者：DATTA, GS; GHOSH, M
  作者单位：State University System of Florida; University of Florida; United States Department of Labor
  摘要：This paper introduces a hierarchical Bayes (HB) approach for prediction in general mixed linear models. The results find application in small area estimation. Our model unifies and extend, a number of models previously considered in this area. Computational formulas for obtaining the Bayes predictors and their standard errors are given in the general case. The methods are applied to two actual data sets. Also, in a special case, the HB predictors are shown to possess some interesting frequenti...
• BELIEF TRANSFORMS AND THE COMPARISON OF HYPOTHESES AI翻译
  作者：GOLDSTEIN, M
  摘要：We describe a general approach to the comparison of two stochastic specifications over a collection of random quantities and then extend the comparison to collections of stochastic specifications. This comparison derives from the eigenstructure of the belief transform, which we construct in full generality for partially specified belief structures. We describe an application of the methodology, namely the comparison of hypotheses. Given various competing probabilistic specifications for a coll...
• SOME PROPERTIES OF THE KAPLAN-MEIER ESTIMATOR FOR INDEPENDENT NONIDENTICALLY DISTRIBUTED RANDOM-VARIABLES AI翻译
  作者：ZHOU, M
  摘要：In this paper we study the Kaplan-Meier estimator in the case where survival and censoring times are not all i.i.d. We prove several results which are analogous to those shown by van Zuijlen in the complete data case.
• BAYES EMPIRICAL BAYES ESTIMATION FOR NATURAL EXPONENTIAL-FAMILIES WITH QUADRATIC VARIANCE FUNCTIONS AI翻译
  作者：WALTER, GG; HAMEDANI, GG
  作者单位：Marquette University
  摘要：Certain orthogonal polynomials are employed to estimate the prior distribution of the parameter of natural exponential families with quadratic variance functions in an approach which combines Bayesian and nonparametric empirical Bayesian methods. These estimates are based on samples from the marginal distribution rather than the conditional distribution.
• RATES OF CONVERGENCE FOR THE ESTIMATES OF THE OPTIMAL TRANSFORMATIONS OF VARIABLES AI翻译
  作者：BURMAN, P
  摘要：We consider here spline estimates of the optimal transformations of variables for multiple correlation and regression as dealt with in a recent paper by Breiman and friedman. We show that we can construct estimates of the optimal transformations which have the same optimal rate of convergence as in the usual nonparametric estimation of a univariate function.
• MAXIMUM-LIKELIHOOD-ESTIMATION OF A SET OF COVARIANCE MATRICES UNDER LOWNER ORDER RESTRICTIONS WITH APPLICATIONS TO BALANCED MULTIVARIATE VARIANCE-COMPONENTS MODELS AI翻译
  作者：CALVIN, JA; DYKSTRA, RL
  摘要：The problem of maximum likelihood estimation of Lowner ordered covariance matrices is considered. It is shown that a dual formulation of this problem is tractable and important in its own right. The interplay between the primal and dual problems suggests a general algorithm for computing the solutions to these problems. This algorithm has application to some estimation problems in balanced multivariate variance components models. The speed of convergence is also discussed for the variance comp...