区域产业投入优化的熵权系数模型研究

针对区域产业投入的优化问题,不仅考虑到投入的经济效益,同时也考虑了投入的社会效益和生态效益,综合主观赋权法和客观赋权法,建立熵权系数模型,以确定各产业的最优投入,并举例说明模型的应用.     

热力学中的态函数熵

本文从热力学角度讨论态函数熵的定义,特点和物理意义以及应用。     

基于熵值法的工作积分制考核标准设计

工作积分制考核能够正向激励员工,提高员工积极性。但在企业实践中,工作积分制容易出现积分标准不公平等问题。本文针对这一问题,将计分标准制定的每个过程进行规范,选择适合的指标体系,采用熵值法构建了绩效积分标准设计模型,以确保积分标准的公平,并给出了测算实例。     

高质量发展指标体系构建及测度——以河北省为例

我国经济已由高速增长阶段转向高质量发展阶段。准确测度经济发展现状,需要构建高质量发展指标体系。根据高质量发展的内涵,构建了包含6个一级指标和24个二级指标构成的高质量发展指标体系,并以河北省为例运用2005-2016年经济运行数据进行实证测算。结果表明,河北省经济发展质量总体呈波动上升态势,但各维度发展并不均衡,经济活力和生态友好两个维度指标持续向好,而创新驱动、结构优化、民生改善这三个维度指标都出现了下滑和较大波动的情况,成为制约高质量发展的短板。     

制造业集聚对新型城镇化的影响研究——基于空间溢出效应的视角

文章依据2014—2020年《国家新型城镇化规划》,构建了中国新型城镇化水平综合评价体系,并基于熵权法测算了2003—2015年中国大陆31个省份新型城镇化水平。在此基础上,通过构建空间杜宾模型,考察了中国制造业集聚的空间交互效应,并在控制了对外出口、金融发展以及财政支出的情况下研究了制造业集聚对新型城镇化的影响。研究结果表明：中国制造业集聚具有显著的空间依赖特征,表现出明显的"集聚俱乐部"现象。制造业集聚显著地推动了中国新型城镇化建设,同时其空间溢出效应明显,在推动本地区新型城镇化的同时还能有力地带动周边地区新型城镇化的发展。地方财政支出的增加有助于显著推动新型城镇化建设,并且地区之间财政行为存在空间互动,邻近地区通过扩大财政支出也能刺激本地区的新型城镇化建设。同时,对外出口和金融发展也是新型城镇化建设中不可或缺的力量,但其空间溢出效应却不明显,并未对周边地区产生明显的影响。对此,建议应该以产业集聚区作为城市功能外溢的核心地区,不断完善集聚区相关配套的基础设施和公共服务体系,实现产城融合的良性发展态势。     

Renyi Entropy Properties of Order Statistics

In this article, we discuss some properties of Renyi entropy and Renyi information of order statistics. Some bounds for Renyi entropy of order statistics are obtained. Also, we relate Renyi entropy ordering of order statistics to Renyi entropy ordering and other well known orderings of parent random variables. Then it is proved that the Renyi information between order statistics and parent random variable is distribution free, and it is shown, as expected, the distance is minimum for the median.     

Minimum and Maximum Information Censoring Plans in Progressive Censoring

Expressions for the entropy, the Kullback-Leibler information, and the I _α-information are established for distributions of progressively Type-II censored order statistics. These results are used to identify minimum and maximum information censoring plans. In particular, we find minimum and maximum entropy plans for DFR, exponential, Pareto, reflected power, and Weibull distributions. The results for Kullback-Leibler and I _α-information hold for any continuous distribution.     

Non parametric portmanteau tests for detecting non linearities in high dimensions

ABSTRACT

We propose two non parametric portmanteau test statistics for serial dependence in high dimensions using the correlation integral. One test depends on a cutoff threshold value, while the other test is freed of this dependence. Although these tests may each be viewed as variants of the classical Brock, Dechert, and Scheinkman (BDS) test statistic, they avoid some of the major weaknesses of this test. We establish consistency and asymptotic normality of both portmanteau tests. Using Monte Carlo simulations, we investigate the small sample properties of the tests for a variety of data generating processes with normally and uniformly distributed innovations. We show that asymptotic theory provides accurate inference in finite samples and for relatively high dimensions. This is followed by a power comparison with the BDS test, and with several rank-based extensions of the BDS tests that have recently been proposed in the literature. Two real data examples are provided to illustrate the use of the test procedure.     

A new generalized normal distribution: Properties and applications

Abstract

The most commonly studied generalized normal distribution is the well-known skew-normal by Azzalini. In this paper, a new generalized normal distribution is defined and studied. The distribution is unimodal and it can be skewed right or left. The relationships between the parameters and the mean, variance, skewness, and kurtosis are discussed. It is observed that the new distribution has a much wider range of skewness and kurtosis than the skew-normal distribution. The method of maximum likelihood is proposed to estimate the distribution parameters. Two real data sets are applied to illustrate the flexibility of the distribution.     

ON THE NULL DISTRIBUTIONS OF THE ENTROPY TESTS FOR THE GAUSSIAN AND INVERSE GAUSSIAN MODELS

Vasicek [1] Vasicek, O. 1976. A test for normality based on sample entropy. J. R. Statist. Soc. B, 38: 54–59.  [Google Scholar]used the “convolution of twelve uniforms” for a Monte Carlo tabulation of the 5% critical values for his entropy test for normality. We employ a superior normal generator to construct a corrected and extended tabulation for his test. Interestingly, it is shown that, the same tables can be used for implementing Mudholkar and Tian's [2] Mudholkar, G. S. and Tian, L. 1999. “An entropy characterization of the inverse Gaussian distribution and related goodness-of-fit test”. In Tech. Rep., University of Rochester Rochester, NY Submitted for publication [Google Scholar]entropy test for the composite inverse Gaussian hypothesis. The finding extends the known Gaussian, inverse Gaussian analogies.