马克思主义按劳分配的精神实质及当代价值

按劳分配是马克思在批判资本主义按生产要素分配的基础上对未来社会收入分配方式的设想。马克思主义按劳分配的精神实质表现为以人为本,劳动的优先性内含着以人为本的精神理念,劳动的平等性体现了以人为本的精神理念,分配的差别性反映了以人为本的精神理念,分配的公平性彰显了以人为本的精神理念。当前我国实行以按劳分配为主体,多种分配方式并存的收入分配制度,深入分析马克思主义按劳分配的精神实质,在收入分配领域就要努力实行劳动优先,认真保障劳动平等,严谨落实分配差别,不断推进分配平等。     

语料库视野下的现代汉语“狗”字义项分布研究

利用北大CCL语料库丰富的语料对“狗”字在现代汉语中的义项分布情况进行了重新分析,发现《现代汉语词典》(第6版)动物词“狗”漏收了“低下、低贱”;“坏”;“坏人,骂人的话”;“奉承,巴结”;“中国的十二生肖之一”等5个义项。     

国有企业内部收入分配公平性研究——基于M公司的案例研究

国有企业内部收入分配是否公平是一个客观现实问题,至今没有给出一个令人信服的答案。本文采用案例研究方法,通过调查和数据收集,分别从薪酬程序的制定、委托代理理论、企业公平理论和社会公平理论的角度,考察国有M公司内部收入分配的公平性问题。从研究结果来看,公司内部薪酬制定程序不公平,企业的收入分配集中于公司管理人员、特别是高层管理人员,管理人员的收入既与企业业绩无关,也与其投入不相称,并且这种分配差距已经到达了社会收入分配的警戒线。本案例研究为判断目前国有企业收入分配和社会收入分配是否公平提供了微观基础。     

Tests of hypotheses on concomitant variables in linear models

The likelihood ratio test for the equality of k univariate normal populations is extended to include the case in which the means are expressed as simple linear regression functions involving two parameters, The moments of the likelihood ratio statistic are derived, and an approximation to the null distribution is obtained.     

On the distributions of the inner distance functions in the multivariate normal populations with unequal covariance matrices

The sample distance functions between an observation and a population were deduced by the likelihood procedures for discrimination problem in the case of several normal populations with unequal covariance matrices(1986). The present paper gives the exact MGFs of the distance functions for the case that the observation and the sample come from the same population and the limiting distributions of the distance functions by using the MCFs.     

Exact-and approximate bayes credibility intervals for the one-way analysis of variance model

In most hierarchical Bayes cases the posterior distributions are difficult to derive and cannot be obtained in closed form. In some special cases, however, it is possible to obtain the exact moments of the posterior distributions.

By applying these moments and Pearson curves or Cornish-Fisher expansions to real problems, good approximations of the exact posterior distributions of individual parameter values as well as linear combinations of parameter values could easily be obtained.     

The folded t distribution

Measurements are frequently recorded without their algebraicsign. As a consequence the underlying distribution of measurements is replaced by a distribution of absolute measurements. When the underlying distribution is t the resulting distribution is called the “folded-t distribution”. Here we study this distribution, we find the relationship between the folded-t distribution and a special case of the folded normal distribution and we derive relationships of the folded-t distribution to other distributions pertaining to computer generation. Also tables are presented which give areas of the folded-t distribution.     

Recurrence relations for moments of record values from generalized extreme value distribution

In this paper some recurrence relations between the moments of record values from the generalized extreme value distribution are established. It is shown that using these recurrence relations, all the single and product moments of all record values can be obtained in a simple recursive manner.     

An alternative reduction formula for the central moments of the general bernoulli distribution

This note presents an alternative to Sproule's (1992) reduction formula for the central mcfnerits of the general Bernoulli distribution, This alternative is founded in part on Roranovsky's (1923) formula for the central moments of the conwentional Binomial distribution, The significance of this note for future research is also discussed.     

Estimation of the Generalized Lambda Distribution Parameters for Grouped Data

Abstract

In this article we consider the problem of fitting a five-parameter generalization of the lambda distribution to data given in the form of a grouped frequency table. The estimation of parameters is done by six different procedures: percentiles, moments, probability-weighted moments, minimum Cramér-Von Mises, maximum likelihood, and pseudo least squares. These methods are evaluated and compared using a Monte Carlo study where the parent populations were generalized lambda distribution (GLD) approximations of Normal, Beta, Gamma random variables, and for nine combinations of sample sizes and number of classes. Of the estimators analyzed it is concluded that, although the method of pseudo least squares suffers from a number of limitations, it appears to be the candidate procedure to estimate the parameters of a GLD from grouped data.