投资模型中收益率的极限定理

利用似然比的概念,研究了投资者关于收益率向量的估计分布和真实分布之间的一些极限性质,得到一类收益率与其估计数学期望的随机偏差定理,即用不等式表示的一类强极限定理.     

关于广义Stein估计的注记

对于一般的正态线性回归模型Ｙ＝Ｘβ＋ε，ε～Ｎｎ（０，σ∑）本文采用极小化均方程差的方法得到了回归系数的一种非线性有偏估计，即广义Ｓｔｅｉｎ估计，给出了它的偏差及其均方误差的渐近展开式，并且在均方误差意义下，当误差干扰充分小（σ→０）时，给出了该估计优于ＢＬＵ估计的渐近充要条件。     

PLM中误差方差未知时的GLR

本文检验部分线性回归模型(PLM)中,误差的方差未知时,函数部分是否是线性函数,在备择假设下,先用局部多项式方法估计出函数部分,再估计参数部分.计算出了零假设下广义似然比(GLR)检验统计量的表达式,给出了它的渐近分布,并对结果进行了模拟.     

数据缺失条件下我国教育收益率估计和分析

教育收益率是指受教育者因增加其受教育的数量而得到的未来净经济报酬的一种测量,它是评价教育生产力的一个非常有用的指数。然而,在收集个人收入数据时,收入往往存在缺失,这为正确估计教育收益率带来了很大的障碍。本文基于我国城镇职工在2002年的年收入数据,在不可忽略缺失假设下,使用明瑟收入函数,研究了我国当年的教育收益率。本文采用Logisitic模型对缺失机制进行拟合,并用联合似然函数方法推断模型中的所有未知参数。该联合似然函数中的参数具有可识别性。假设估计量是相合的,我们证明了估计量的渐近正态性。在不可忽略缺失机制下所得的教育收益率为9.6%,符合预期。     

多元线性模型参数的部分压缩估计

考虑多元线性回归模型Y=XB ε,其中E(Vec(ε))=0,Cov(Vec(ε))=∑In,当设计阵X呈病态时,模型参数的LS估计不再是一个优良估计,为此,提出了一种部分压缩估计,并分析了其性质.     

异质性、自选择偏差和教育收益率

采用广义选择修正法,在考虑异质性和自选择偏差问题基础之上,结合最新的调查数据,评估了我国2006年高等教育收益率,并与传统模型下的研究结果进行了比较.同时还分析了其他非实验数据效应评估模型在本文的适用性.研究结果表明,随着经济改革深化和劳动市场的完善,2006年的高等教育收益率较之前有了显著的提高.另外,还发现可观察的异质性不明显,但不可观察的异质性和自选择偏差选择显著存在,且人们会根据自己的比较优势选择是否接受高等教育.     

债券年收益率的计算方法

购买债券，作为一种投资方式，已越来越为广大公众所认识和接受。但对于如何计算债券年收益率，人们了解得却甚少，这里向大家提供几个计算债券年收益率的基本公式及珠算一盘清计算法，供珠友们参考。     

一种使用奇异值分解的岭估计

本文使用矩阵奇异值分解的技术，得到了线性回归模型的设计阵的一个较好的逼近，在此基础上，给出了回归系数的一种使用奇异值分解的岭估计，能够减少由于设计阵的病态所引起的麻烦。     

关于广义压缩最小二乘估计的注记

本文研究了广义压缩最小二乘估计（ＧＳＬＳＥ）的一些性质，给出了它的均方误差（ＭＳＥ）的一个无偏估计量（ＵＥ），采用极小该ＵＥ的方法确定了ＧＳＬＳＥ的参数选取公式，并把这个统一化的方法应用于广义岭估计，岭估计、Ｍａｓｓｙ主成分估计、Ｓｔｅｉｎ型压缩估计以及根方有偏估计等，从而得到了它们的一种选取参数的方法，最后，结合Ｈａｌｄ实例进行比较分析，结果表明，本文的方法是实用的，有效的。     

纵向数据广义部分线性模型的惩罚GMM估计

对纵向数据的部分线性模型,通常的做法是用样条方法或者核方法逼近非参数部分,然后再用广义估计方程的估计方法去估计参数部分.本文使用P-样条拟合非参数函数,对不同的矩条件用不同的广义矩方法对模型的参数和非参数进行估计,并且给出了估计量的大样本性质;并用计算机模拟和实例证明了当模型中存在不同的矩条件时,采用不同的惩罚广义矩方法可以显著地提高估计精度.     

Analysis of ordered categorical data to develop control charts for monitoring customer loyalty

In the highly competitive business environment of today, the cost to attract new customers is much higher than the cost required to maintain the existing ones. To keep the balance between the acquisition rate and defection rate through executing offensive and defensive marketing policies, it is required to have real time information using an efficient method to monitor customer loyalty. The relationship between customer loyalty and customer satisfaction should be kept in mind when one develops a method for loyalty monitoring. This paper presents several control charts classified in two groups based on the scale used to assess customer loyalty. In the first group of control charts, customer loyalty is considered as a binary random variable modeled by Bernoulli distribution whilst in the second group, an ordinal scale is considered to report loyalty level. Performance comparison of the proposed techniques using ARL criterion indicates that chi‐square and likelihood‐ratio control charts developed based on Pearson chi‐square statistic and ordinal logistic regression model respectively are able to rapidly detect the significant changes in loyalty behavior. To show how to apply the procedures and how to interpret their results, two illustrative synthetic cases are also explained. Copyright © 2009 John Wiley & Sons, Ltd.     

Tests for nonparametric parts on partially linear single index models

Tests for nonparametric parts on partially linear single index models are considered in this paper. Based on the estimates obtained by the local linear method, the generalized likelihood ratio tests for the models are established. Under the null hypotheses the normalized tests follow asymptotically the χ2-distribution with the scale constants and the degrees of freedom being independent of the nuisance parameters, which is called the Wilks phenomenon. A simulated example is used to evaluate the performances of the testing procedures empirically.     

中国银行间拆借利率扩散模型的极大拟似然估计

本文用极大拟似然估计法估计了中国银行间市场七天拆借利率扩散模型的参数。并用自助法对众多不同的模型进行了广义拟似然比检验。结论表明:中国货币市场利率具有均值回复效应:利率敏感系数γ值为1.421265,对利率水平具有较高敏感性。     

上证综合指数收益率的统计分析

本就上证综合指数收益率是否服从正态分布给出两种具体检验方法。得出了上证综合指数收益率分布具有尖峰和厚尾的特性，因此实际中指数收益率服从正态分布的假设是不合理的。从而用能反映尖峰厚尾特征的t分布进行拟合。得出上证综合指数收益率符合t3分布。     

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??This paper constructs a penalized empirical likelihood estimation method via quadratic inference function method, filter method and empirical likelihood estimation method. Under some regular conditions, we derived the large sample properties of estimators and show that the proposed empirical likelihood ratio is asymptotically to chi-square distribution. Furthermore, the infinite sample performance of the proposed method is evaluated by Monte Carlo simulation and real data analysis.     

Penalized Empirical Likelihood Estimation for Partially Linear Single Index Panel Model with Fixed Effects

This paper constructs a penalized empirical likelihood estimation method via quadratic inference function method, filter method and empirical likelihood estimation method. Under some regular conditions, we derived the large sample properties of estimators and show that the proposed empirical likelihood ratio is asymptotically to chi-square distribution. Furthermore, the infinite sample performance of the proposed method is evaluated by Monte Carlo simulation and real data analysis.     

Regression type tests for parametric hypotheses based on optimally selected subsets of the order statistics

Through use of a regression framework, a general technique is developed for determining test procedures based on subsets of the order statistics for both simple and composite parametric null hypotheses. Under both the null hypothesis and sequences of local alternatives these procedures are asymptotically equivalent in distribution to the generalized likelihood ratio statistic based on the corresponding order statistics. A simple, approximate method for selecting quantiles for such tests, which endows the corresponding test statistics with optimal power properties, is also given.