论国际航空运输侵权责任的发展——以1999年《蒙特利尔公约》为视角

在分析《蒙特利尔公约》的产生原因和发展过程的基础上,采用比较和归纳的方法,总结了国际航空运输侵权责任的发展趋势,认为国际航空侵权的归责原则由推定过失责任向严格责任发展,损害赔偿范围不断扩大。目前,中国的航空运输侵权责任立法主要存在归责原则僵化及责任限额过低的缺陷,因此有关立法应修改归责原则和提高责任限额。     

论我国未成年人犯罪刑事立法的若干规定

犯罪低龄化及未成年人犯罪已成为一个全球性的严重社会问题,亦是国际社会普遍关注的社会现象,同时也是各国政府致力于研究预防和减少犯罪的首要环节。由于未成年人有着独特的身心特点,因此,如何有效地预防和遏制未成年人犯罪,成为包括我国在内的世界各国刑事法律关注的焦点。     

A bivariate noncentral T-disttrtoution with applications

The particular bivariate noncentral t-distribution associated with two univariate noncentral t variates having a correlation coefficient of one is considered. Some applications and properties are presented together with tables in the same form as Johnson and Welch's tables for a univariate noncentral t-distribution.     

Some Properties of the Exact and Score Methods for Binomial Proportion and Sample Size Calculation

In this article, we point out some interesting relations between the exact test and the score test for a binomial proportion p. Based on the properties of the tests, we propose some approximate as well as exact methods of computing sample sizes required for the tests to attain a specified power. Sample sizes required for the tests are tabulated for various values of p to attain a power of 0.80 at level 0.05. We also propose approximate and exact methods of computing sample sizes needed to construct confidence intervals with a given precision. Using the proposed exact methods, sample sizes required to construct 95% confidence intervals with various precisions are tabulated for p = .05(.05).5. The approximate methods for computing sample sizes for score confidence intervals are very satisfactory and the results coincide with those of the exact methods for many cases.     

Asymptotic Efficiency in Parametric Structural Models with Parameter‐Dependent Support

In certain auction, search, and related models, the boundary of the support of the observed data depends on some of the parameters of interest. For such nonregular models, standard asymptotic distribution theory does not apply. Previous work has focused on characterizing the nonstandard limiting distributions of particular estimators in these models. In contrast, we study the problem of constructing efficient point estimators. We show that the maximum likelihood estimator is generally inefficient, but that the Bayes estimator is efficient according to the local asymptotic minmax criterion for conventional loss functions. We provide intuition for this result using Le Cam's limits of experiments framework.