试谈亚里士多德的幸福理论

亚里士多德是古希腊最杰出的哲学家,幸福理论是亚里士多德道德理论的核心。本文通过对亚里士多德关于幸福的概念、性质及其中道原则在幸福实现中的作用等方面内容的阐述,探讨亚里士多德幸福观的现代启示。     

从体用关系角度理解儒家的道德论述——兼论当代儒学的核心价值观

在中国哲学史上,＂道＂的概念是一个富有理性的具有本体意义的哲学范畴。儒、墨、道、法诸家均然。但百家所论之＂道＂的涵义各不相同。儒家的＂道＂是集政治、伦理、道德功能于一体的本体性概念,有多种涵义,而最重要、最根本的是以＂道＂为根本之德,是人生的根本原则、政治的最高理想和治国安民的战略。儒家之＂德＂,是指对＂道＂的体悟、实践,是＂道＂的具体表现形式。在儒家思想逻辑中,道、德关系实质上是体用关系,＂道＂是根本之德,是＂体＂,＂德＂是道之体现,是用。在儒学诸多价值观念中,最重要的核心价值观念是＂仁＂,儒学的根本之道就是＂仁＂道。＂仁＂与其他德目（如义、礼、智、信、和、敬等）的关系,不是并列关系,而是体用关系。仁是道之体,义、礼、智、信、和、敬等是道之用。历代儒家对儒学核心价值观的概括,就根本之道而言,都指仁道。但对体现＂仁＂道的＂常德＂,认识不尽一致,有四维、五行、六德、八德诸说。文章认为,从立足于当今时代的精神需求、同时又最具普世性的价值视野而言,还是以＂一道（仁道）五德（义礼信和敬）＂来概括儒学的核心价值观比较恰当。现代社会的精神危机与道德失落,正在呼唤儒学的核心价值。作为＂以道自任＂的儒者,应该自觉承担起弘道责任,为弘扬儒学的道德人文精神、为建设民主文明、多元和谐的的未来世界而克尽其责!     

孟子“仁义”伦理思想略论

从孟子伦理思想的内在逻辑看,性善论、仁政思想、义利观和道德修养论是相互联系、相互影响的一个整体。这几个方面以“性善论”为理论基础,以“内圣外王”为主线,以道德修养论为实现“内圣”的基本路径,以仁政为实现“外王”的方略,突显“仁义”伦理的思想特质,构建了一个系统性很强的思想理论体系。     

Comparisons of tests of distributional assumption in Poisson regression model

Count data consists of discrete non-negative integer values. Poisson regression model is one of the most popular model used to model count data. This model assumes that response variable has Poisson distribution. The purpose of this article is to assess distributional assumption of this model by using some goodness of fit tests. These tests are compared in respect to type I error and power rates of tests with different samples, parameters and sample sizes. Simulation study suggests that the most powerful tests are generally Dean–Lawless and Cameron–Trivedi score tests.     

儒家生命伦理的精神、模式及特性——对“易道生生”的义理解读

儒家伦理从根本上来说就是“生”的伦理，“生”是儒家伦理的基本精神。儒家围绕着“生”造就了一个天人互动的生命模式，并以天、命、性、道诸概念逻辑架构出一个相应的生命义理体系。这一体系在形上的维度首先表现为天人一体的宇宙观和“易道生生”的生命观，并以此为依据，形成了颇有儒家特色的“继天为善”的伦理观和“各正性命”的身心工夫论。     

An entropy-based test for goodness of fit of the von mises distribution

The maximum entropy characterization of the von Mises distribution on the circle is exploited to derive a consistent goodness of fit test for the von Mises distribution. Monte Carlo simulation results are tabulated giving critical values of the test statistic for various sample sizes and values of the concentration parameter. A power analysis is presented for various alternative hypotheses, comparing this entropy statistic to two other competing goodness of fit statistics. The entropy statistic is shown to compare favorably and may be more attractive, especially considering its ease of computation.     

Evaluation of Beta Generation Algorithms

In this article, we discuss the maximum likelihood estimates (MLEs) for the exponential and Weibull distributions by considering progressive Type-I interval censored data. For exponential distribution, the explicit expression of MLE of failure rate cannot be obtained when the intervals are not equal in length. The direct application of some numerical algorithms, such as the Newton–Raphson algorithm, is non-ideal because of the cumbersome second derivative. We apply some equivalent quantities to obtain the MLE of failure rate of exponential distribution. Based on the equivalent quantities and the Weibull-to-exponential transformation technique, we propose a new algorithm to obtain the MLEs for the parameters of progressive Type-I interval Weibull data. An example reanalysis and some simulation studies are carried out to illustrate the performance of the estimations using the new algorithm.     

Statistical Analysis for the Inverse Trinomial Distribution

This article considers parameter estimation, goodness of fit, likelihood ratio and score tests, and model selection by Akaike information criterion for the inverse trinomial (IT) distribution, a classical one-dimensional random walk distribution. The IT distribution has a cubic variance function of the mean and is a generalization of the negative binomial distribution. Basic distributional properties and expressions for the probability mass function, recurrence formula, moments, and score functions are also presented.     

A moment test to identify uniformity

An omnibus test of uniformity based upon the ratios of sample moments and population moments is introduced. Results of a monte carlo power study show that for two types of alternatives considered, the proposed test has good power in comparison with Neyman's test N ₂Greenwood's test, Kolmogorov-Smirnov test, and Chi-squared test.