Estimation of 2-D ARMA model parameters by using equivalent AR approach

In this paper, the problem of estimating the parameters of a two-dimensional autoregressive moving-average (2-D ARMA) model driven by an unobservable input noise is addressed. In order to solve this problem, the relation between the parameters of a 2-D ARMA model and their 2-D equivalent autoregressive (EAR) model parameters is investigated. Based on this relation, a new algorithm is proposed for determining the 2-D ARMA model parameters from the coefficients of the 2-D EAR model. This algorithm is a three-step approach. In the first step, the parameters of the 2-D EAR model that is approximately equivalent to the 2-D ARMA model are estimated by applying 2-D modified Yule-Walker (MYW) equation to the process under consideration. Then, the moving-average parameters of the 2-D ARMA model are obtained solving the linear equation set constituted by using the EAR coefficients acquired in the first step. Finally, the autoregressive parameters of the 2-D ARMA model are found by exploiting the values obtained in first and second steps. The performance of the proposed algorithm is compared with other 2-D ARMA parameter and spectral estimation algorithms available in the technical literature by means of three different criteria. As a result of this comparison, it is shown that the parameters and the corresponding power spectrums estimated by using the proposed algorithm are converged to the original parameters and the original power spectrums, respectively.     

巴斯卡分布NB(r,p)中参数r的估计

巴斯卡分布NB（r,p)是重要的离散型分布之一，当r已知时，巴斯卡分布NB（r,p)中未知参数p(p∈（0，1））的估计是众所周知的。本文分别在p已知和未知的条件下，研究了参数r(r∈（1，2，…}）的估计，并得到了它们的渐近性质。     

Robust estimator design with an emphasis balance between performance and robustness

From a number of ML estimators (typically unbiased) of practical interest which include the variance for a Gaussian distribution, the standard deviation for a Laplace distribution, the variance for a Rayleigh distribution and a “spread parameter” for a Cauchy distribution, we design robust estimators according to an emphasis balance between normalized performance and normalized robustness. We measure performance with inverted MSE and robustness with a differential geometric approach.     

A large-scale donor attempt to improve educational status of the poor and household income distribution: The experience of PEDC in Vietnam

In 2003, donors combined together in Vietnam to support the provision of quality primary schooling for 226 disadvantaged districts (about a third of the country). US$160 million was invested in infrastructure, materials and training across the 226 districts. The programme has been commended by donors and received good press inside Vietnam. Comparison of achievement surveys in 2001 and 2007 showed, however, that there had been a decline in performance in the targeted districts. This article explores various hypotheses as to how this could have happened; and in particular the increasing amounts spent by better-off households on their children's education.     

不同运动方式对P53、TIGAR、HKII基因表达和乳酸含量的影响

目的:比较不同训练方式对P53、TIGAR、HKII基因表达和乳酸含量的影响。方法:30只大鼠随机分为安静组(C)、耐力训练组(E)、间歇性冲刺训练组(F),训练6周。最后一次训练结束后24~48 h内切取腓肠肌检测P53、TIGAR、HKIImRNA转录和P53、TIGAR的蛋白表达以及乳酸含量。结果:1)E组、F组与C组相比、E组和F组相比P53mRNA转录、蛋白表达水平均没有显著性差异。2)E组TIGARmRNA和蛋白表达明显高于C组,而F组与C组相比、F组与E组相比TIGARmRNA和蛋白表达均没有显著性差异。3)E组、F组与C组相比、E组和F组相比HKIImRNA表达均没有显著性差异。4)E组与C组相比、E组与F组相比乳酸含量没有显著性差异,F组乳酸含量非常显著高于C组。结论:1)两种训练方式都不能影响P53基因表达。2)耐力训练可能抑制了糖酵解促进了线粒体的有氧呼吸。3)两种训练方式对血糖稳态的有力控制对保持机体正常生理功能发挥具有重要意义。4)耐力训练在一定程度上抑制了P53调节的糖酵解信号通路,而间歇性冲刺训练似乎对该通路没有明显的影响。     

金融危机企业资产负债表模型对我国的适用性检验-基于动态面板数据模型的分析

摘要：本文根据我国522家制造业上市公司2001-2007年的财务数据,建立动态面板数据模型,分析了Krugman(1999)提出的金融危机企业资产负债表模型对我国的适用性。研究结论认为,在企业存在货币错配的情况下,人民币汇率波动对企业的短期信贷能力有显著的影响,但对长期信贷能力的影响还不明显。而且,这种影响是动态的,人民币汇率波动的滞后1期值比当期值对企业信贷能力的影响更加明显。因而,金融危机企业资产负债表模型对我国具有适用性。       

基于物元模型和区间模糊数贴近度的企业与软件匹配性研究

如果企业和软件系统能很好的匹配,可以更好的实现两个物元之间的目的和功能.文章从平衡计分卡的角度选择全方位的匹配指标体系,但各个指标值不是一个确定的数值,而是一个区间模糊数,并且从区间模糊数的特性出发构建企业和软件系统各个匹配指标的贴近度,再应用熵值客观赋权法给各指标赋权,最后综合计算企业与软件的总贴近度即匹配度,文中给出了匹配过程具体的计算步骤和实例,希望能给决策者以科学的参考依据.     

小麦保险费率厘定:基于小波分析与非参数估计法

合理厘定保险费率是农作物保险开展的重要前提,可为政府保费补贴等支农政策提供决策依据.本文以北京市冬小麦为样本,采用小波分析和非参数估计方法相结合的方法,改进了农作物保险纯费率厘定方法,提高了计算结果的合理性与准确性,即,利用小波分析法确定作物单产的趋势产量,并在非参数高斯函数为核密度函数设定,借助Silverman的"经验法则”确定带宽,确定了样本数据的概率分布模型,最终完成了北京市冬小麦保险纯费率厘定过程.     

泊松分布中参数的经典估计与Bayes估计的相等关系

文中证明了泊松分布中未知参数的矩估计和最大似然估计,一定存在一个先验分布,使其贝叶斯估计就是该经典估计的结论.     

识别含水层参数的单纯形-混沌优化算法

以泰斯公式为基础,将单纯形-混沌优化算法应用于分析抽水试验数据,求解含水层参数函数优化问题。采用具有搜索速度快、局部搜索能力强等优点的单纯形算法与全局搜索能力强的混沌优化算法结合的单纯形-混沌优化算法。数值实验结果表明：单纯形-混沌优化算法可有效地应用于求解含水层参数函数优化问题;待估参数导水系数的初始取值范围、粗搜索次数和混沌序列长度对算法的收敛速度有一定的影响,但不会影响算法的收敛性。