Parameter Estimation for the NEAR（p） Model

As to the acronym NEAR(p), it means "New Exponential Autoregressive Process of order p". The NEAR(p) model is denned by where α0,α1,α2… are non-negative and sum to unity, and the residual sequence{εt} is defined as where q1, q2, … , qp+1 are non-negative and sum to unity, and {Et} is an independent and identically distributed (i.i.d.) sequence of standard exponential variants. Chan showed necessary and sufficient conditions for the existence of a stationary and ergodic NEAR(p) model.     

Empirical Likelihood Ratio Confidence Interval for Positively Associated Series

Empirical likelihood is discussed by using the blockwise technique for strongly stationary,positivelyassociated random variables.Our results show that the statistics is asymptotically chi-square distributed andthe corresponding confidence interval can be constructed.     

AR（p）模型中的缺失数据估计

运用EM算法,对含有缺失数据的AR（p）模型进行参数估计,通过最大似然准则就非左端缺失的情况进行插补.最后,用蒙特卡洛方法给出实验分析,表明如下结果：（i）误差与AR模型的阶数正相关,与缺失比例正相关;（ii）当AR模型的特征根模长相对较小时,误差与数据长度负相关,且误差被控制在了标准差的30％以内;（iii）当模长中等时,误差基本控制在1个标准差左右;（iv）当模长较大时,误差与数据长度正相关,而且误差也相对较大.     

Empirical likelihood for AR-ARCH models based on LAD estimation

By employing the empirical likelihood method,confidence regions for the stationary AR(p)-ARCH(q) models are constructed.A self-weighted LAD estimator is proposed under weak moment conditions.An empirical log-likelihood ratio statistic is derived and its asymptotic distribution is obtained.Simulation studies show that the performance of empirical likelihood method is better than that of normal approximation of the LAD estimator in terms of the coverage accuracy,especially for relative small size of observation.     

MA$(q)$模型的经验似然推断

In this article we study the empirical likelihood inference for MA（q） model. We propose the moment restrictions, by which we get the empirical likelihood estimator of the model parameter, and we also propose an empirical log-likelihood ratio based on this estimator. Our result shows that the EL estimator is asymptotically normal, and the empirical log-likelihood ratio is proved to be asymptotical standard chi-square distribution.     

基于经验似然的AR(p)模型的统计诊断

本文基于经验似然方法对AR(p)模型进行统计诊断,文章首先给出p阶自回归模型的广义估计函数并对模型参数进行估计,然后运用数据删失、局部影响分析和伪残差方法对AR(p)模型进行统计诊断,最后通过实证来说明该诊断方法的有效性.     

正态AR(1)模型参数极大似然估计的精确解

本文对正态ＡＲ（１）模型，当Ｒ０已知，且时，证明了极大似然估计存在，但不唯一，这与Ｒ０，Ｒ１两个参数整体求极大似然估计的结果有本质上的不同，同时还研究了极大似然估计（）的数学特性与解析表达式．     

序约束下AR(p)-ARCH(q)模型参数的估计与检验

In this paper, we study a stationary AR(p)-ARCH(q) model with parameter vectors a and β. We propose a method for computing the maximum likelihood estimator (MLE) of parameters under the nonnegative restriction. A similar method is also proposed for the case that the parameters are restricted by a simple order: α1≥α2≥…≥αq, andβ1≥β2≥…βp. The strong consistency of the above two estimators is discussed. Furthermore, we consider the problem of testing homogeneity of parameters against the simple order restriction. We give the likelihood ratio (LR) test statistic for the testing problem and derive its asymptotic null distribution.     

The Law of Iterated Logarithm of Rescaled Range Statistics for AR（1） Model

Let {Xn,n ≥ 0} be an AR（1） process. Let Q（n） be the rescaled range statistic, or the R/S statistic for {Xn} which is given by （max1≤k≤n（∑j=1^k（Xj - ^-Xn）） - min 1≤k≤n（∑j=1^k（ Xj - ^Xn ））） /（n ^-1∑j=1^n（Xj -^-Xn）^2）^1/2 where ^-Xn = n^-1 ∑j=1^nXj. In this paper we show a law of iterated logarithm for rescaled range statistics Q（n） for AR（1） model.     

纵向数据均值和协方差矩阵的有效稳健估计（英文）

本文提出一种针对纵向数据回归模型下的均值和协方差矩阵同时进行的有效稳健估计.基于对协方差矩阵的Cholesky分解和对模型的改写,我们提出一个加权最小二乘估计,其中权重是通过广义经验似然方法估计出来的.所提估计的有效性得益于经验似然方法的优势,稳健性则是通过限制残差平方和的上界来达到.模拟研究表明,和已有的针对纵向数据的稳健估计相比,所提估计具有更高的效率和可比的稳健性.最后,我们把所提估计方法用来分析一组实际数据.     

Empirical Likelihood Inference for Functional Coefficient ARCH-M Model

Empirical likelihood inference for parametric and nonparametric parts in functional coefficient ARCH-M models is investigated in this paper. Firstly, the kernel smoothing technique is used to estimate coefficient function δ(x). In this way we obtain an estimated function with parameter β.Secondly, the empirical likelihood method is developed to estimate the parameter β. An estimated empirical log-likelohood ratio is proved to be asymptotically standard chi-squred, and the maximum empirical likelihood estimation(MELE) for β is shown to be asymptotically normal. Finally, based on the MELE of β, the empirical likelihood approach is again applied to reestimate the nonparametric part δ(x). The empirical log-likelohood ratio for δ(x) is proved to be also asymptotically standard chi-squred. Simulation study shows that the proposed method works better than the normal approximation method in terms of average areas of confidence regions for β, and the empirical likelihood confidence belt for δ(x) performs well.     

右删失数据下非线性回归模型的经验似然推断

考虑随机右删失数据下非线性回归模型,提出了模型中未知参数的调整的经验对数似然比统计量.在一定的条件下,证明了.所提出的的统计量具有渐近χ~2分布,由此结果构造了兴趣参数的置信域.通过模拟研究,对经典的经验似然、调整的经验似然和非线性最小二乘方法在有限样本下进行了比较,并对氯离子浓度试验数据进行了分析.     

具有AR(1)误差的均值漂移模型的Score检验和似然比检验

讨论了具有AR(1)误差的线性均值漂移模型,研究了自相关性的检验问题,导出了关于误差相关性的Score检验统计量和似然比检验统计量,并把它推广到误差项为AR(1)非线性均值漂移模型.本文还给出了一个数值例子说明检验方法的实用性.     

泊松回归模型中协变量含误差的经验似然推断

在模型的协变量含有测量误差的情况下,考虑一类泊松回归模型的统计推断问题.通过巧妙地构造辅助随机向量,提出一个工具变量类型的经验似然统计推断方法.证明构造的经验对数似然比函数渐近服从标准卡方分布,进而给出了回归系数的置信区间.所提出的估计方法可以有效地消除测量误差对估计精度的影响,并且具有较好的有限样本性质.     

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For linear quantile regression model, this paper proves that the test statistics, besed on smoothed empirical likelihood (SEL) method and least absolute deviation (LAD) method, both converge weakly to a noncentral Chi-square distribution under the local alternatives $H_1:\beta=\beta_0+a_n$, where $\beta$ is the true parameter. Simulation results show that the SEL method is more efficient than the LAD method.     

语音识别中AR模型的研究

介绍用线性AR(p)模型提取语音信号的LPC参数估计的方法(矩(YW)估计和极大似然(M LE)估计),并且对模型进行检验和模拟.     

经验似然统计推断方法发展综述

本文在介绍经验似然方法的基础上，进一步介绍这一方法在统计推断中的应用，具体地介绍了这一方法在总体均值推断、线性模型推断、分位数推断、估计方程推断及利用辅助信息进行推断等几种重要统计推断中的应用，同时也介绍了这一方法最近在不完全数据中的应用及由此所提出的被估计、被调整及bootstrap经验似然方法。     

基于双AR(p)模型的股价分析及其实证研究

在双AR(p)模型的基础上,选取了具有代表性的沪深300指数,并对其部分股市收盘价序列进行了平稳化处理,研究了近期中国股市的股价波动.在双.AR(p)模型严平稳条件下进行了模型诊断,最后通过动态预测得出双AR(p)模型可用于股价预测的结论.