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991.
John H.J. Einmahl 《统计学通讯:理论与方法》2013,42(4):813-822
The asymptotic distribution of the sup-norm of the heavily weighted empirical process is established in the multidimensional case. This theorem extends in particular the famous result in Jaeschke (1975, 1979) to higher dimensions. There is a striking difference between the behaviour for higher dimensions and that for dimension one, especially the limiting distribution is now a simple transformation of a standard exponential random variable. 相似文献
992.
K. G. Janardan 《统计学通讯:理论与方法》2013,42(9):2167-2179
Janardan (1973) introduced the generalized Polya-Eggenberger distribution as a limiting form of the generalized Markov-Polya distribution (GMPD), Ja¬nardan (1998) derived GPED formally by means of Lagrange's expansion and discussed its various properties systematically. Here, a new urn model is pro¬vided for the GPED. Moment estimators of the parameters are given in closed form. Maximum hkelihood estimators are also given. Some apphcations are provided. 相似文献
993.
994.
This article addresses the problem of testing the null hypothesis H0 that a random sample of size n is from a distribution with the completely specified continuous cumulative distribution function Fn(x). Kolmogorov-type tests for H0 are based on the statistics C+ n = Sup[Fn(x)?F0(x)] and C? n=Sup[F0(x)?Fn(x)], where Fn(x) is an empirical distribution function. Let F(x) be the true cumulative distribution function, and consider the ordered alternative H1: F(x)≥F0(x) for all x and with strict inequality for some x. Although it is natural to reject H0 and accept H1 if C + n is large, this article shows that a test that is superior in some ways rejects F0 and accepts H1 if Cmdash n is small. Properties of the two tests are compared based on theoretical results and simulated results. 相似文献
995.
B. N. Pandey 《统计学通讯:理论与方法》2013,42(9):2191-2202
The present paper investigates the properties of a testimator of scale of an exponential distribution under Linex loss function. The risk function of testimator is derived and compared with that of an admissible estimator relative to Linex loss function. The shrinkage testimator is proposed which is the extension of testimator and its properties have been discussed. The level of significance of testimator is decided on the basis of Akaike information criterion following Hirano (1977, 1978). It is found that the testimator and shrinkage testimator dominates the admissible estimator in terms of risk in certain parametric space. 相似文献
996.
《统计学通讯:理论与方法》2013,42(8):1309-1333
ABSTRACT The search for optimal non-parametric estimates of the cumulative distribution and hazard functions under order constraints inspired at least two earlier classic papers in mathematical statistics: those of Kiefer and Wolfowitz[1] and Grenander[2] respectively. In both cases, either the greatest convex minorant or the least concave majorant played a fundamental role. Based on Kiefer and Wolfowitz's work, Wang3-4 found asymptotically minimax estimates of the distribution function F and its cumulative hazard function Λ in the class of all increasing failure rate (IFR) and all increasing failure rate average (IFRA) distributions. In this paper, we will prove limit theorems which extend Wang's asymptotic results to the mixed censorship/truncation model as well as provide some other relevant results. The methods are illustrated on the Channing House data, originally analysed by Hyde.5-6 相似文献
997.
《统计学通讯:理论与方法》2013,42(9):1457-1465
ABSTRACT In the empirical Bayes (EB) decision problem consisting of squared error estimation of the failure rate in exponential distribution, a prior Λ is placed on the gamma family of prior distributions to produce Bayes EB estimators which are admissible. A subclass of such estimators is shown to be asymptotically optimal (a.o.). The results of a Monte Carlo study are presented to demonstrate the a.o. property of the Bayes EB estimators. 相似文献
998.
999.
《统计学通讯:理论与方法》2013,42(12):2123-2137
ABSTRACT A two parameter extended form of standard gamma function is suggested which provide extra flexibility to the density function over positive range. A finite mixture of beta distribution is defined by using the suggested extended form. The shape of density function of extended gamma distribution and also that of finite mixture of beta distribution for various values of the parameters are shown. Inverted distribution of extended gamma and that of finite mixture of beta distribution are given. 相似文献
1000.
Maximum likelihood estimation of parameter structures for the Wishart distribution using constraints
Maximum likelihood estimation under constraints for estimation in the Wishart class of distributions, is considered. It provides a unified approach to estimation in a variety of problems concerning covariance matrices. Virtually all covariance structures can be translated to constraints on the covariances. This includes covariance matrices with given structure such as linearly patterned covariance matrices, covariance matrices with zeros, independent covariance matrices and structurally dependent covariance matrices. The methodology followed in this paper provides a useful and simple approach to directly obtain the exact maximum likelihood estimates. These maximum likelihood estimates are obtained via an estimation procedure for the exponential class using constraints. 相似文献