1992

最新文章

• A GENERAL RESAMPLING SCHEME FOR TRIANGULAR ARRAYS OF ALPHA-MIXING RANDOM-VARIABLES WITH APPLICATION TO THE PROBLEM OF SPECTRAL DENSITY-ESTIMATION AI翻译
  作者：POLITIS, DN; ROMANO, JP
  作者单位：Stanford University
  摘要：In 1989 Kunsch introduced a modified bootstrap and jackknife for a statistic which is used to estimate a parameter of the m-dimensional joint distribution of stationary and alpha-mixing observations. The modification amounts to resampling whole blocks of consecutive observations, or deleting whole blocks one at a time. Liu and Singh independently proposed (in 1988) the same technique for observations that are m-dependent. However, many time-series statistics, notably estimators of the spectral...
• TESTING GOODNESS-OF-FIT IN REGRESSION VIA ORDER SELECTION CRITERIA AI翻译
  作者：EUBANK, RL; HART, JD
  摘要：A new test is derived for the hypothesis that a regression function has a prescribed parametric form. Unlike many recent proposals this test does not depend on arbitrarily chosen smoothing parameters. In fact, the test statistic is itself a smoothing parameter which is selected to minimize an estimated risk function. The exact distribution of the test statistic is obtained when the error terms in the regression model are Gaussian, while the large sample distribution is derived for more general...
• ASYMPTOTICS FOR M-ESTIMATORS DEFINED BY CONVEX MINIMIZATION AI翻译
  作者：NIEMIRO, W
  摘要：We consider M-estimators defined by minimization of a convex criterion function, not necessarily smooth. Our asymptotic results generalize some of those concerning the LAD estimators. We establish a Bahadur-type strong approximation and bounds on the rate of convergence.
• FROM THE SPECIES PROBLEM TO A GENERAL COVERAGE PROBLEM VIA A NEW INTERPRETATION AI翻译
  作者：LO, SH
  作者单位：Harvard University
  摘要：A basic interpretation is given which provides a new way of understanding the structure of the species problem and which leads to the popular Turing-Good-Robbins estimator. Through this interpretation we provide an explanation why the Turing-Good-Robbins estimators are always biased. An iterative procedure is suggested and applied to these estimators, which leads to new estimators whose biases are reduced. Using this basic construction we are able to generalize our discussion to a much broader...
• USING STOPPING RULES TO BOUND THE MEAN INTEGRATED SQUARED ERROR IN DENSITY-ESTIMATION AI翻译
  作者：MARTINSEK, AT
  摘要：Suppose X1, X2,..., X(n) are i.i.d. with unknown density f. There is a well-known expression for the asymptotic mean integrated squared error (MISE) in estimating f by a kernel estimate f(n), under certain conditions on f, the kernel and the bandwidth. Suppose that one would like to choose a sample size so that the MISE is smaller than some preassigned positive number w. Based on the asymptotic expression for the MISE, one can identify an appropriate sample size to solve this problem. However,...
• ON THE CONSTRUCTION OF ASYMMETRICAL ORTHOGONAL ARRAYS AI翻译
  作者：HEDAYAT, AS; PU, KW; STUFKEN, J
  作者单位：Baxter International Inc; Iowa State University
  摘要：General techniques for the construction of asymmetrical orthogonal arrays of strength 2 are presented. These are then applied to special cases to obtain new families of such arrays. Among these are saturated main-effect plans based on s(m) runs with factors at s(v)i levels, i = 0, 1,..., r, where m greater-than-or-equal-to v(r), v0 = 1, v(i-1) divides v(i), i = 1, 2,..., r, and s is a prime power.
• MINIMUM HELLINGER-TYPE DISTANCE ESTIMATION FOR CENSORED-DATA AI翻译
  作者：YING, ZL
  摘要：A Hellinger-type distance for hazard rate functions is defined. It is used to obtain a class of minimum distance estimators for data that are subject to a possible right censorship. The corresponding score process is shown to be approximated by a martingale, which is exploited to obtain the asymptotic normality under considerably weaker conditions than those normally assumed for minimum Hellinger distance estimators. It is also shown that under the parametric assumption the estimators are asym...
• MULTIVARIATE LOCATION ESTIMATION USING EXTENSION OF R-ESTIMATES THROUGH U-STATISTICS TYPE APPROACH AI翻译
  作者：CHAUDHURI, P
  作者单位：University of Wisconsin System; University of Wisconsin Madison
  摘要：We consider a class of U-statistics type estimates for multivariate location. The estimates extend some R-estimates to multivariate data. In particular, the class of estimates includes the multivariate median considered by Gini and Galvani (1929) and Haldane (1948) and a multivariate extension of the well-known Hodges-Lehmann (1963) estimate. We explore large sample behavior of these estimates by deriving a Bahadur type representation for them. In the process of developing these asymptotic res...
• EFFICIENT ESTIMATES IN SEMIPARAMETRIC ADDITIVE REGRESSION-MODELS WITH UNKNOWN ERROR DISTRIBUTION AI翻译
  作者：CUZICK, J
  摘要：Several authors have shown how to efficiently estimate-beta in the semiparametric additive model y = x'-beta + g(t) + error, g(t) smooth but unknown when the error distribution is normal. However, the general theory suggests that efficient estimation should be possible for general error distributions with finite Fisher information even when the error distribution is unknown. In this note we construct a sequence of estimators which achieves this goal under technical assumptions.
• THE ADMISSIBILITY OF THE LINEAR INTERPOLATION ESTIMATOR OF THE POPULATION TOTAL AI翻译
  作者：MEEDEN, G
  摘要：Consider the problem of estimating the total of some finite population. Suppose the labels attached to the units of the population are such that members of the population whose labels are close together are more alike than units whose labels are far apart. For such a population a sensible estimator of the population total is one that interpolates linearly between successive members of the sample. The admissibility of this estimator will be demonstrated. The related interval estimators will be ...