复合LINEX对称损失函数下Burr分布参数的估计

文章在参数a已知,双参数Burr分布参数的先验分布为其共轭先验分布T（a,b）时,给出了Burr分布参数在复合LINEX对称损失函数下的Bayes估计和多层Bayes估计。     

基于区间型数据的城市居民家庭资产分布研究

文章利用调查数据研究发现,我国地级以上城市家庭的资产分布具有“双峰”特征.因此复合分布函数形式更适合描述城市居民家庭的资产分布状况.采用参数估计的方法发现由sm分布和Burr分布构成的复合分布函数最接近城市家庭资产的真实分布,据此测算的基尼系数为0.5132.对比以往的研究得出:我国城市居民家庭资产分布的不平等程度在逐步扩大的同时,城市家庭中的中产阶层拥有财富的比例也在减少.极端贫困的家庭拥有资产的状况略有改观.     

熵损失函数下Burr(α)X分布参数的贝叶斯估计

文章研究了Burr(α)X分布参数的各类贝叶斯估计问题.在熵损失函数下分别获得了参数的贝叶斯估计、经验贝叶斯估计、多层贝叶斯估计和E-Bayes估计.证明了参数经验贝叶斯估计的渐近最优性,讨论了参数多层贝叶斯估计和E-Bayes估计的稳健性,通过蒙特卡洛方法对各类估计的MSE进行了数值模拟和比较分析,结果表明:经验贝叶斯估计的均方误差最小,精度较高.     

客户需求分布的非线性统计分析模型

文章提供了一种统计分析模型,能够对高新技术设备制造商研究客户构成及其资产规模分布和营业规模分布提供帮助,使厂家能以低成本和及时快捷的方式获得特定客户需求信息。此模型利用国家发布的社会经济统计资料,数据来源准确,易在企业咨询中推广应用。     

国内上市公司品牌经营效应实证研究

自上世纪80年代以来,国内外理论界对品牌进行了深入研究,但实证研究相对较少。文章选取使用中国驰名商标或获得中国名牌产品认定的国内上市公司作为研究对象,借助2001年年报数据资料,分析了国内上市公司品牌经营现状,分析了名牌上市公司的地区分布和行业分布。文章运用均值(中值)比较、曼·惠特尼U检验方法,对全体名牌上市公司和非名牌上市公司各盈利能力指标和成长性指标进行对比分析,发现品牌经营确实显著提高了企业营业利润增长率;但企业盈利能力、业务拓展能力的提高并不显著。通过对制造业上市公司进一步分析,发现在竞争较为充分的行业,品牌经营能显著提高企业的盈利能力和成长性。     

公司多元化程度、规模化与企业绩效——基于上市公司的实证研究

本文根据沪深两地97家上市公司2001～2005年连续5年年报数据,对97上市公司多元化经营、企业规模与企业绩效进行了实证研究。研究表明：我国上市公司多元化程度与企业绩效并没有显著的相关性,多元化程度与企业规模水平存在一定的正相关性,企业规模对企业的经营绩效有显著的正相关性。最后,对其产生的原因进行了分析,并提出有针对性的建议。     

上市公司关联交易中避税行为的实证研究

文章从关联交易的规模与类型两方面,通过建立面板数据固定效应模型,检验了粉饰型关联交易对会计-税收差异的影响.检验结果显示:从交易规模看,企业粉饰型关联交易规模越大,会计-税收差异越大,说明企业在粉饰型关联交易中确实存在明显的避税行为;从交易类型看,企业粉饰型资金类关联交易越多,会计-税收差异越大,说明资金类关联交易避税程度较高.     

我国城市规模发展水平分析与比较研究

城市规模发展是城市化研究的重要问题之一。最早在古希腊时的亚里士多德就已经开始注意并研究了城市规模的发展问题。 2 0世纪以来 ,由于世界城市化发展迅速 ,不仅城市数量在急剧增加 ,城市规模也在不断扩大 ,于是城市规模发展水平问题的研究就被日益重视起来。在我国随着城市化速度的加快 ,城市规模发展水平问题的研究也被提到议事日程上来。城市发展规模究竟多大为适度 ,命理水平应该如何 ,它与城市规模效率、城市规模分布、城市可续发展能力等有着密切关系。为此 ,本文将对此进行实证分析 ,以便为我国制定城市发展政策 ,探讨城市发展规模…     

中国电子信息行业上市公司董事结构与公司绩效的实证研究

从四个维度出发,在特定法律规范约束下,引入绝对合理独立董事人数概念,对2010年中国电子信息业171家上市公司董事会结构和企业绩效的关系进行了研究,结果显示:中国电子信息产业上市公司董事会规模大的企业绩效优于规模小的企业,规模较小时企业绩效不稳定;企业绩效并不直接取决于独立董事占董事会的比重,而与独立董事超过绝对合规独立董事人的比例有关;由于职业经理人市场不完善,董事长与总经理两职合一的企业绩效优于两职分离的企业;对董事会适当的股权激励将增加董事工作的积极性.     

国有经济产业分布与产业绩效的非线性关联研究

我国国有经济的产业分布是否提高了相关产业的绩效?这一问题目前学术界并没有形成统一认识。利用中国制造业29个产业的相关数据,建立面板门限模型,研究上述问题。研究发现国有经济产业分布比例的增加对产业技术效率会由正向影响变成反向影响。同时产业规模对产业技术效率的影响会由于国有经济产业分布状况的不同产生不同方向的影响。     

Economic-statistical design of X ¥ charts for non-normal data by considering quality loss

When the X ¥ control chart is used to monitor a process, three parameters should be determined: the sample size, the sampling interval between successive samples, and the control limits of the chart. Duncan presented a cost model to determine the three parameters for an X ¥ chart. Alexander et al. combined Duncan's cost model with the Taguchi loss function to present a loss model for determining the three parameters. In this paper, the Burr distribution is employed to conduct the economic-statistical design of X ¥ charts for non-normal data. Alexander's loss model is used as the objective function, and the cumulative function of the Burr distribution is applied to derive the statistical constraints of the design. An example is presented to illustrate the solution procedure. From the results of the sensitivity analyses, we find that small values of the skewness coefficient have no significant effect on the optimal design; however, a larger value of skewness coefficient leads to a slightly larger sample size and sampling interval, as well as wider control limits. Meanwhile, an increase on the kurtosis coefficient results in an increase on the sample size and wider control limits.     

Modelling the diameter distribution of forest stands using the Burr distribution

SUMMARY For the past 20 years, forest modellers have largely used the Weibull distribution to summarize diameter distributions and to predict timber volume in a forest at clearfell time. The wider family of Burr distributions is investigated here as an alternative to the Weibull distribution. Using data from 20 permanent sample plots of Pinus radiata, we compare Burr and Weibull fits, showing that the Burr distribution enhances precision by roughly 13 . The effectiveness of the Burr distribution for prediction is found to be similar to that of the Weibull distribution.     

Recurrence relations for moments of progressive type-II right censored order statstics from burr distribution

In this paper some recurrence relations between moments of progressive Type-II right censored order statistics from doubly truncated Burr distribution are established. These recurrence relations would enable one to obtain all the single and product moments of Burr progressive Type-II right censored order statistics in a simple recursive manner.     

Bayesian Prediction of the Median of the Burr Distribution with Fixed and Random Sample Sizes

sLingappaiah (1986) was the first to introduce the idea of Bayesian prediction in life testing when the size of the future sample is a random variable. In this paper we discuss the Bayesion prediction of the sample median when the parent distribution is a generalized Burr distribution (GBD), the old sample is censored type II and the size of the future sample is a random variable. A numerical illustration is provided.     

Bayesian prediction with a random sample size for the burr lifetime distribution

This paper is concerned with the problem of deriving Bayesian prediction bounds for the Burr distribution when the sample size is a random variable. Prediction bounds for both the future observations (the case of two-sample prediction) and the remaining observations in the same sample (the case of one-sample prediction) will be derived. The analysis will depend mainly on assuming that the size of the sample is a random variable having the Poisson distribution. Finally, numerical examples are given to illustrate the results.     

Optimal B-robust estimators for the parameters of the Burr XII distribution

The Burr XII distribution offers a flexible alternative to the distributions that play important role for modelling data in reliability, risk and process capability. However, estimating the shape parameters of the Burr XII distribution is a challenging problem. The classical estimation methods such as maximum likelihood and least squares are often used to estimate the parameters of the Burr XII distribution, but these methods are very sensitive to the outliers in the data. Thus, a robust estimation method alternative to the classical methods is needed to find robust estimators that are less sensitive to the outliers in the data. The purpose of this paper is to use the optimal B-robust estimation method [Hampel FR, Ronchetti EM, Rousseeuw PJ, Stahel WA. Robust statistics: the approach based on influence functions. New York: Wiley; 1986] to obtain robust estimators for the shape parameters of the Burr XII distribution. The simulation results show that the optimal B-robust estimators generally outperform the classical estimators in terms of the bias and root mean square errors when there are outliers in data.     

Robust regression for estimating the Burr XII parameters with outliers

The Burr XII distribution offers a more flexible alternative to the lognormal, log-logistic and Weibull distributions. Outliers can occur during reliability life testing. Thus, we need an efficient method to estimate the parameters of the Burr XII distribution for censored data with outliers. The objective of this paper is to present a robust regression (RR) method called M-estimator to estimate the parameters of a two-parameter Burr XII distribution based on the probability plotting procedure for both the complete and multiply-censored data with outliers. The simulation results show that the RR method outperforms the unweighted least squares and maximum likelihood methods in most cases in terms of bias and errors in the root mean square.     

Another extended Burr III model: some properties and applications

We introduce an extended Burr III distribution as an important model for problems in survival analysis and reliability. The new distribution can be expressed as a linear combination of Burr III distributions and then it has tractable properties for the ordinary and incomplete moments, generating and quantile functions, mean deviations and reliability. The density of its order statistics can be given in terms of an infinite linear combination of Burr III densities. The estimation of the model parameters is approached by maximum likelihood and the observed information matrix is derived. The proposed model is applied to a real data set to illustrate its potentiality.     

Discrete Burr and discrete Pareto distributions

In this paper we obtain discrete Burr and Pareto distributions using the general approach of discretizing a continuous distribution and propose them as suitable lifetime models. It may be worth exploring the possibility of developing discrete versions of the Burr and Pareto distributions, so that, the same can be used for modeling discrete data. The equivalence of continuous and discrete Burr distributions has been established. Some important distributional properties and estimation of reliability characteristics are discussed. An application in reliability estimation in series system and a real data example on dentistry using this distribution is also discussed.     

The four-parameter Burr XII distribution: Properties,regression model,and applications

This paper introduces a new four-parameter lifetime model called the Weibull Burr XII distribution. The new model has the advantage of being capable of modeling various shapes of aging and failure criteria. We derive some of its structural properties including ordinary and incomplete moments, quantile and generating functions, probability weighted moments, and order statistics. The new density function can be expressed as a linear mixture of Burr XII densities. We propose a log-linear regression model using a new distribution so-called the log-Weibull Burr XII distribution. The maximum likelihood method is used to estimate the model parameters. Simulation results to assess the performance of the maximum likelihood estimation are discussed. We prove empirically the importance and flexibility of the new model in modeling various types of data.