试论「～と会う」和「～に会う」的用法和区别

在学习和运用日语过程中 ,格助词是比较难以准确掌握和运用的 ,人们往往习惯从格助词本身去分析其语法功能。从动词词义决定其格助词在句子中的构式的角度看 ,格助词 [と ]表示行为动作的共同主体 ,格助词[に ]表示行为动作的承受者。进一步说 [～と会う ]所表达的这一 [会う ]的行为动作是双方共同的行为动作。[～に会う ]所表达的这一 [会う ]的行为动作是单方面的行为动作 ,另一方是这一行为动作的承受者     

GMM tests for the Katz family of distributions

Generalized method of moments (GMM) is used to develop tests for discriminating discrete distributions among the two-parameter family of Katz distributions. Relationships involving moments are exploited to obtain identifying and over-identifying restrictions. The asymptotic relative efficiencies of tests based on GMM are analyzed using the local power approach and the approximate Bahadur efficiency. The paper also gives results of Monte Carlo experiments designed to check the validity of the theoretical findings and to shed light on the small sample properties of the proposed tests. Extensions of the results to compound Poisson alternative hypotheses are discussed.     

Robustness of a Class of Partial Diallel Cross Designs to the Unavailability of a Complete Block of Observations

Complete and partial diallel cross designs are examined as to their construction and robustness against the loss of a block of observations. A simple generalized inverse is found for the information matrix of the line effects, which allows evaluation of expressions for the variances of the line-effect differences with and without the missing block. A-efficiencies, based on average variances of the elementary contrasts of the line-effects, suggest that these designs are fairly robust. The loss of efficiency is generally less than 10%, but it is shown that specific comparisons might suffer a loss of efficiency of as much as 40%.     

悼红轩里增删遍,料定知音旷代存——拜读贺信民先生《红情绿意——<红楼梦>点面论》

三十多年的耕耘,《红情绿意——〈红楼梦〉点面论》的面世,成为贺信民先生贡献于红学界的又一丰硕成果。书中宏观运幄与微观烛照兼长,用生命体验来感悟红楼,在慧眼洞察的缕缕新意之中折射着贺信民先生“研红”的风雨征程,折射着红学界积火传薪的优良学术传承。     

阿盟发展缺失及其对上合组织的启示

阿拉伯国家联盟是当今世界成立最早的几个地区性国际组织之一。在其六十多年的发展历程中,从维护阿拉伯国家整体利益来看,其成绩并不理想。本文对阿盟的发展缺失的表现及其原因进行了分析,并探索了其对上海合作组织完善和发展过程中的启示。     

Automobile prices and protection: The U.S.-Japan trade restraint

We examine the effects of the U.S.-Japan trade restraint on automobile prices and quality upgrading, for both Japanese imports and American small cars. From April 1981 to April 1984 the suggested retail price of all Japanese models increased by 15.8 percent, or 5.3 percent per year. We find that nearly the entire amount of this rise can be explained by the upgrading of individual models. This upgrading may benefit consumers who would purchase a luxury import in any case, but harms those who desire the basic imports. In addition to upgrading, we conclude that a second cost of the trade restraint has been to prevent the yen depreciation from being passed onto American consumers, in terms of lower imported auto prices. For U.S. small cars we find a 9.1 percent rise in the suggested retail price, or 3 percent per year, with a fraction of this amount due to model upgrading. If the yen depreciation had led to lower import prices without the trade restraint, then we expect that U.S. auto prices would have been lower, too.     

Goodness of fit for the inverse Gaussian distribution

For testing the fit of the inverse Gaussian distribution with unknown parameters, the empirical distribution-function statistic A² is studied. Two procedures are followed in constructing the test statistic; they yield the same asymptotic distribution. In the first procedure the parameters in the distribution function are directly estimated, and in the second the distribution function is estimated by its Rao-Blackwell distribution estimator. A table is given for the asymptotic critical points of A². These are shown to depend only on the ratio of the unknown parameters. An analysis is provided of the effect of estimating the ratio to enter the table for A². This analysis enables the proposal of the complete operating procedure, which is sustained by a Monte Carlo study.     

A Bayesian method for classification and discrimination

We discuss Bayesian analyses of traditional normal-mixture models for classification and discrimination. The development involves application of an iterative resampling approach to Monte Carlo inference, commonly called Gibbs sampling, and demonstrates routine application. We stress the benefits of exact analyses over traditional classification and discrimination techniques, including the ease with which such analyses may be performed in a quite general setting, with possibly several normal-mixture components having different covariance matrices, the computation of exact posterior classification probabilities for observed data and for future cases to be classified, and posterior distributions for these probabilities that allow for assessment of second-level uncertainties in classification.     

Deconvolution with supersmooth distributions

Nonparametric deconvolution problems require one to recover an unknown density when the data are contaminated with errors. Optimal global rates of convergence are found under the weighted L_p-loss (1 ≤ p ≤ ∞). It appears that the optimal rates of convergence are extremely low for supersmooth error distributions. To resolve this difficulty, we examine how high the noise level can be for deconvolution to be feasible, and for the deconvolution estimate to be as good as the ordinary density estimate. It is shown that if the noise level is not too high, nonparametric Gaussian deconvolution can still be practical. Several simulation studies are also presented.