学术编辑的思维特征

学术编辑的思维持征 ,既有别于一般期刊编辑 ,亦有别于文艺作品编辑。抽象性、客观性、指导性、规范性、创造性和逻辑性是其主要特征。学术编辑只有具备敏锐的超前意识和强烈的社会责任感、勇于开拓的创造意识和鲜明的创新意识、博专合一的编辑业务能力及掌握现代信息技术的意识与能力 ,才能使学术编辑真正不辱使命 ,名实相副     

On testing exponentiality against new better than used of specified age

R.M. Hollander, D.H. Park and F. Proschan [A class of life distributions for aging, J. Amer. Statist. Assoc. 81 (1986) 91–95] introduced the concept of the larger class of life distributions called new better than used of specified age. In practice, one might be interested in the new better than used behaviour at an unknown but estimable age t₀. Here, we investigate the testing of new better than used of specified age t₀ (NBU-t₀) alternatives. A class of test statistics for testing NBU-t₀ (t₀ is known) based on a U-statistic whose kernel depends on sub-sample minima is proposed. A member of the class of tests proposed by N. Ebrahimi and M. Habbibullah [Testing whether the survival distribution is new better than used of specified age, Biometrika 77 (1990) 212–215] for this problem belongs to the class of tests proposed here. The distributional properties of the class of test statistics are studied. The performances of a few members of the proposed class of tests are studied in terms of Pitman asymptotic relative efficiency. The Pitman ARE values show that the members of the class perform well in comparison with the N. Ebrahimi and M. Habbibullah [Testing whether the survival distribution is new better than used of specified age, Biometrika 77 (1990) 212–215] tests. The proposed class of tests is shown to be consistent for NBU-t₀ alternatives.     

Exchangeability,predictive sufficiency and Bayesian bootstrap

Summary Let {X _n } be a sequence of random variables conditionally independent and identically distributed given the random variable Θ. The aim of this paper is to show that in many interesting situations the conditional distribution of Θ, given (X ₁,…,X _n ), can be approximated by means of the bootstrap procedure proposed by Efron and applied to a statisticT _n (X ₁,…,X _n ) sufficient for predictive purposes. It will also be shown that, from the predictive point of view, this is consistent with the results obtained following a common Bayesian approach.     

On asymptotic normality of likelihood and conditional analysis

The likelihood function from a large sample is commonly assumed to be approximately a normal density function. The literature supports, under mild conditions, an approximate normal shape about the maximum; but typically a stronger result is needed: that the normalized likelihood itself is approximately a normal density. In a transformation-parameter context, we consider the likelihood normalized relative to right-invariant measure, and in the location case under moderate conditions show that the standardized version converges almost surely to the standard normal. Also in a transformation-parameter context, we show that almost sure convergence of the normalized and standardized likelihood to a standard normal implies that the standardized distribution for conditional inference converges almost surely to a corresponding standard normal. This latter result is of immediate use for a range of estimating, testing, and confidence procedures on a conditional-inference basis.     

RECENT TRENDS IN ASYMPTOTIC OPTIMAL INFERENCE FOR DEPENDENT OBSERVATIONS1

An overview of some recent developments in the area of asymptotic inference for non-ergodic type stochastic processes is presented. Both local and global formulations of the asymptotic model are given, and non-local optimality results are reviewed. Recent results on conditional inference are briefly discussed. Some open problems and possibilities for new developments are also mentioned.     

The asymptotic distribution of the likelihood ratio when the model is incorrect

Classical results on the asymptotic distribution of the likelihood ratio statistic rely on the assumption that the model chosen to construct the test statistic be correct. The model is said to be correct if it contains the true distribution of the observations. In this paper the asymptotic distribution of the likelihood ratio statistic is derived without the condition that the model need be correct.     

A nonparametric test for Type I censored data: r samples

This paper is concerned with testing that r random samples are all from the same population when the data are left (or right) censored. A statistic is developed which has elements of a goodness-of-fit statistic and of a modified Kruskal-Wallis statistic. The efficiency of this statistic relative to some other commonly used statistics is calculated. Some Monte Carlo comparisons are given.     

ON THE GLOBAL ASYMPTOTIC STABILITY OF THE EQUATION +f+h+g(x)=0

This paper gives a sufficient criterion of the global asymptotic stability of the zerosolution of the equation(?)+f((?))+h((?))+g(x)=0     

ASYMPTOTIC MINIMAX PROPERTIES OF L-ESTIMATORS OF SCALE

This paper asks whether or not the efficient L-estimator of scale corresponding to the least informative distribution in ε-contamination and Kol-mogorov neighbourhoods of certain distributions possesses the saddlepoint property. This is of interest since the saddlepoint property implies the mini-max property, namely, that the supremum of the relative asymptotic variance of an L-estimator is minimized by the efficient estimator corresponding to that member of the distributional class with minimum Fisher information for scale. Our findings are negative in all cases investigated.