Negative moments of a modified power series distribution and bias of the maximum likelihood estimator

The class of Modified Power Series distributions (MPSD) containing Lagrangian Poisson (LPD) (Consul and Jain, 1973) and Lagrangian binomial distributions (LBD) (Jain and Consul, 1971) was studied by Gupta (1974). We investigate the problem of finding the negative momentsE[X^-r ], of displaced and decapitated Modified Power Series Distributions. We derive the relationship between rand (r-1) negative moments. The negative moments of the decapitated and displaced LPD are obtained. These results are, then, used to find the exact amount of bias in the ML estimators of the parameters in the LPD and the LBD. We have also given the variances of the ML estimator and the minimum variance unbiased estimator of the parameter in the LPD.     

购买力平价（PPP）测算方法研究评述与展望

购买力平价（PPP）可为发行不同货币的国家间比较提供比汇率法更加可靠的数据基础,因此其在国际经济比较领域的应用日益广泛。本文对现有的PPP测算方法按照指数法和随机法两大板块进行了综述,包括了传统的EKS法、最小间隔树法、链式法、星形法、平均价格法、原始CPD法、CPRD法等基本方法,以及此后发展的加权EKS法、特征CPD法、空间CPD法和加权CPD法,简要评述了这些方法的基本思想及各自的优缺点。随后,本文详尽总结了两大类方法的发展脉络,深入探讨了这些方法的适用性问题,并作了研究展望。     

基于因素模型的协高阶矩矩阵估计及其应用研究

在高阶矩投资组合中,使用传统样本估计方法会产生较高估计误差和模型设定误差。本文在多因素模型的基础上,给出一种改进的协高阶矩估计方法,分析了基于多因素模型压缩估计量的渐进一致性。蒙特卡洛模拟表明,多因素压缩估计量在有限样本中具有更小的平均绝对误差、根均方误差以及更高的平均绝对改进百分比,有效提高了协高阶矩矩阵估计的精度;即使在样本观测量比资产数目少时,估计的协高阶矩矩阵精度都会有较大提高。基于2005年6月至2019年5月沪深300成分股的高阶矩投资组合实证发现,多因素压缩方法与其他估计方法相比,在年化收益率上可以获得4.7%～32.8%的提升,最大回撤能够下降3.7%～18.3%,表明使用多因素压缩估计方法构建的投资组合有更大的可能获得更多货币效用增益,以及面临亏损时,产生的最大亏损更小。该方法有助于金融机构或理性投资者在进行投资组合时减小投资损失,获得更好的投资回报。     

Estimation in two-parameter exponential distributions

Exponential distributions are used extensively in the field of life-testing. Estimation of parameters is revisited in two-parameter exponential distributions. A comparison study between the maximum likelihood method, the unbiased estimates which are linear functions of the maximum likelihood method, the method of product spacings, and the method of quantile estimates are presented. Finally, a simulation study is given to demonstrate the small sample properties     

内生结构突变下的突变点确定方法与单位根检验研究 ——基于残差平方和最小值确定突变点的比较分析

 对于内生突变情形下的单位根检验,突变点的确定方法会影响到单位根检验的功效,不同方法在确定突变点位置时的表现也不尽相同。本文首先评述了几种常用的突变点确定方法及相应的单位根检验,然后对基于各类回归式残差平方和最小值确定突变点的方法进行了比较分析,本文所设数据生成过程有别于已有研究,并首次考虑了依据可行广义最小二乘（FGLS）估计来确定突变点。在此基础上,还对比分析了几种不同突变点确定方法下的单位根检验功效和实际检验水平。结论显示,依据FGLS残差平方和最小值得到准确突变点的频率最高,且在AO模型下据此进行Perron检验具有较高的功效且不会发生较大的水平扭曲。     

复共线条件下普通岭估计的改进

本文通过对普通岭估计缺陷的分析,提出了改进岭估计的“部分修正”的方法。这一方法既降低了过度膨胀的均方误差,使回归参数得到合理压缩,同时又降低了岭估计过大的均方残差。     

浅谈对Pitman准则的认识

Pitman准则是估计理论中仅有的几个比较两个估计优劣的标准之一 ,本文着重从Pitman准则的局限性、合理性及可发展性这三个方面浅谈了对Pitman准则的看法及认识 ,并在文 [1]的基础上给出了判断估计子 ^ 是否是Pitman意义下的最优估计一种判断方法     

Bayesian prediction of the total time on test using doubly censored rayleigh data

In a Bayesian setting, and on the basis of a doubly censored random sample of failure times drawn from a Rayleigh distribution, Fernandez (2000, Statist. Probab. Lett. , 48 , 393-399) considered the problem of predicting an independent future sample from the same distribution. In this article, we extend his work to include the estimation of the predictive distribution of the total time on test up to a certain failure in a future sample, as well as that of the remaining testing time time until all the items in the original sample have failed. Two examples are used to illustrate the prediction procedure.