Bootstrap LM Tests for Spatial Dependence in Panel Data Models with Fixed Effects

This paper applies bootstrap methods to LM tests(including LM-lag test and LM-error test) for spatial dependence in panel data models with fixed effects, and removes fixed effects based on orthogonal transformation method proposed by Lee and Yu(2010). The consistencies of LM tests and their bootstrap versions are proved, and then some asymptotic refinements of bootstrap LM tests are obtained. It shows that the convergence rate of bootstrap LM tests is O((N T)~(-2)) and that of fast double bootstrap LM tests is O((NT)~(-5/2)). Extensive Monte Carlo experiments suggest that,compared to aysmptotic LM tests, the size of bootstrap LM tests gets closer to the nominal level of signifiance, and the power of bootstrap LM tests is higher, especially in the cases with small spatial correlation. Moreover, when the error is not normal or with heteroskedastic, asymptotic LM tests suffer from severe size distortion, but the size of bootstrap LM tests is close to the nominal significance level.Bootstrap LM tests are superior to aysmptotic LM tests in terms of size and power.     

具有未知跳跃股票价格异方差性的 Bootstrap模拟检验

采用Bootstrap模拟方法检验股票价格异方差性．利用随机分析方法获得波动率的一个渐进估计，这种估计能够消除股票价格中可能存在的随机跳跃的影响，并且无需确定波动率函数的具体形式、建立了一个关于波动率为常数的原假设的统计量，用Bootstrap模拟方法可以获得该统计量的分布．用此检验方法对中国沪深两市指数进行检验，获得了两市中指数呈异方差性的结论．这种检验方法对认识市场微观结构、资产定价、投资和风险管理都具有积极作用．     

平滑转移模型线性检验的可靠性研究

提出了将自助法(bootstrap)的不同变体应用于平滑转移自回归模型的线性检验,并通过蒙特卡罗实验分别考察其在误差项独立同分布和存在序列相关时的有限样本性质.重点研究了非线性参数和序列相关系数对检验水平和功效的影响.实验结果表明,基于自助法的线性检验在各样本容量下都具有更高的功效,并且可以很好地纠正基于极限分布理论的LST统计量的水平扭曲.本文还详细介绍快速了两阶段自助法(FDB)的基本思想和实现方法,模拟实验证明它比基本自助法具有更好的稳健性和收敛性.     

Empirical Analysis of Value-at-Risk Estimation Methods Using Extreme Value Theory

1. INTroDUCTIONFinancial institutes often hold asset portfolios consisting of bonds, stock, etc., whose values often vary due tothe change of market factors such as interest rate and exchange rate. The induence on the value of portfoliosmade by the bad variation of majrket factors is watched specially by the financial institutes. That is to say, it isnecessary to estimate the probability and degree of the decrease in the value of portfolios during a given timeperiod. As an integrated frame…     

ASYMPTOTIC THEORIES FOR THE ROBUST PP ESTIMATORS OF THE PRINCIPAL COMPONENTS AND DISPERSION MATRIX——Ⅲ.BOOTSTRAP CONFIDENCE SETS,BOOTSTRAP TESTS

In this paper the bootstrap theories,which are based on the author's former paper,ofM-typ eprincipal components and dispersion matrices and M-type PP tests for multivariate locationand scale are obtained.The bootstrap confidence sets for the principal components,dispersionmatrices and correlation matrices are also constructed.     

维纳过程寿命预测的一种自助法

针对传统的维纳过程寿命预测方法未能有效考虑产品总体和个体之间的差异问题, 提出了解决该问题的一种自助法. 首先, 利用正态分布来描述产品总体维纳过程退化模型 的漂移参数和扩散参数; 然后, 对个体的性能退化参数进行自助估计并得到多组自助样本; 最后, 根据个体退化参数的自助样本对总体退化参数的分布进行估计, 获取其多组自助样本 并对总体的寿命进行预测. 通过对某航天长寿命产品的实例分析验证了该方法的有效性.     

构造脉冲响应函数的置信区间的新方法

提出一个构造近单位根自回归过程脉冲响应函数的置信区间的新方法。新方法首先利用近似中位数无偏估计方法修正自回归系数的普通最小二乘估计的偏差,然后利用标准自举方法构造脉冲响应函数的置信区间。蒙特卡罗模拟结果表明在小样本时新方法的表现要明显优于已有的方法。     

用于时间序列数据建模的多模态模糊认知图

针对单一模型难以准确反映时间序列多种变化模态的问题,提出了一种基于模糊认知图的时间序列数据多模态建模方法.该方法使用随机自助法选取多个子序列,以包含各种变化模态.在各个子序列上分别建立子模糊认知图模型.使用粒计算方法对子模型进行有效融合;并分析了不同权重策略融合的性能.所建立的模型不仅可以对时间序列数据进行数值及区间预...     

Monitoring Mean and Variance Change-Points in Long-Memory Time Series

This paper proposes two ratio-type statistics to sequentially detect mean and variance change-points in the long-memory time series. The limiting distributions of monitoring statistics under the no change-point null hypothesis, alternative hypothesis as well as change-point misspecified hypothesis are proved. In particular, a sieve bootstrap approximation method is proposed to determine the critical values. Simulations indicate that the new monitoring procedures have better finite sample performance than the available off-line tests when the change-point nears to the beginning time of monitoring, and can discriminate between mean and variance change-point. Finally, the authors illustrate their procedures via two real data sets: A set of annual volume of discharge data of the Nile river, and a set of monthly temperature data of northern hemisphere. The authors find a new variance change-point in the latter data.

     

极值理论(EVT)方法用于受险价值(VaR)计算的实证比较与分析

讨论了根据极值理论 ( EVT)计算受险价值 ( Va R)的两类不同的方法 :基于矩估计的“两次子样试算法”和极大似然估计法 ,并给出了各自理论推导过程和计算步骤 .同时 ,把这两类方法与正态分布和经验分布的结果进行了比较 .应用四种汇率历史数据进行的实证计算表明 ,在极端条件下 ,用极值理论方法估计 Va R具有很高的准确性 ,而矩估计法的结果又优于极大似然估计法 .     

Bootstrap Estimation from Simulation Outputs

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概率天气预报的K近邻非参数估计仿真模型

基于模式识别和相似预报思想，提出了一种制作概率天气预报的K近邻非参数估计仿真模型(简称KNN-M)。该模型包括历史样本数据库、近邻子集搜索程序、近邻子集优化算法和预报量估计技术。利用该模型进行了降水和云量的概率预报试验，独立样本检验结果表明，该模型预报稳定性好，预报准确率较高，具有较好的业务应用前景。     

Statistical Inference for a Simple Step Stress Model with Competing Risks Based on Generalized Type-Ⅰ Hybrid Censoring

This paper investigates a simple step-stress accelerated lifetime test(SSALT) model for the inferential analysis of exponential competing risks data. A generalized type-I hybrid censoring scheme is employed to improve the efficiency and controllability of the test. Firstly, the MLEs for parameters are established based on the cumulative exposure model(CEM). Then the conditional moment generating function(MGF) for unknown parameters is set up using conditional expectation and multiple integral techniques. Thirdly, confidence intervals(CIs) are constructed by the exact MGF-based method, the approximate normality-based method, and the bias-corrected and accelerated(BCa) percentile bootstrap method. Finally, we present simulation studies and an illustrative example to compare the performances of different methods.     

A ROBUSTNESS ANALYSIS OF THE MUSIC AND THE MINIMUM－NORM ALGORITHMS WITH RESPECT TO CORRELMED NOISE

ＡＲＯＢＵＳＴＮＥＳＳＡＮＡＬＹＳＩＳＯＦＴＨＥＭＵＳＩＣＡＮＤＴＨＥＭＩＮＩＭＵＭ－ＮＯＲＭＡＬＧＯＲＩＴＨＭＳＷＩＴＨＲＥＳＰＥＣＴＴＯＣＯＲＲＥＬＭＥＤＮＯＩＳＥ￥ＪＩＡＰｅｉｚｈａｎｇ（ＩｎｓｔｉｔｕｔｅｏｆＳｙｓｔｅｍｓＳｃｔｅｎｃｅ，Ａｃ...     

A METHOD TO APPROXIMATE DISTRIBUTIONSOF RELATED STATISTICS

1.IntroductionandResultSupposethereisand--dimensional(d21)randomsampleXi,fromsomeprobabilityspace(fi,I,P)to(R',B,),Xi4Fi,Fibeingunknown,15i5n,n21.Whatconcernsusisthedistributionalpropertyofsomep-dimensional(p21)statisticTi~Ti(XIt''IX.;FI1'',Fi)whichisus…     

基于厚尾分布的非寿险准备金评估模型

未决赔款准备金评估是财产保险公司偿付能力管理的核心工作,通常使用的评估方法是广义线性模型.当增量赔款数据存在尖峰厚尾特征时,广义线性模型的传统分布假设可能与实际数据不相符合.此外,保险公司的多条业务线之间往往存在一定的相依关系,这就要求对总准备金的评估结果进行相应调整.本文使用三种新的厚尾分布(即幂Frechet分布、广义对数Moyal分布和全尾伽马分布)代替传统模型中使用的伽马分布、对数正态分布和GB2分布假设,考察它们在未决赔款准备金评估中的应用效果,并应用Copula函数描述了不同业务线之间的相依关系.借助参数化bootsrap和蒙特卡罗随机模拟方法,给出了准备金的预测分布和风险度量值.基于一组实际数据的研究结果表明,厚尾分布对于改善未决赔款准备金的预测效果具有很高的应用价值,而相依性的调整也使得准备金的预测结果更加合理.     

BOOTSTRAPPING PP L-STATISTICS FOR TESTS

Some bootstrap approximations of the asymptotic distributions of PP L-statistics whichwere proposed by the authors in[7]are discusse.Bootstrap statistics and their asymptotic propertiesare established.Two examples and the numerical results are given,by which one can actuallyimplement the proposed tests under the condition of normal population.     

SOME NEW RESULTS ON THE CONFIDENCELIMITS FOR RELIABILITY PARAMETERS IN THECASE OF NO FAILURES

1.IntroductionDenotethelifelengthofanyitemofsomekindofproductbyX.ThedistributionfunctionofXisF(t)(F(0)=0).Asiswellknown,themostimportantreliabilitypametersare:(1)R(t)=1--F(t)(reliatiility);(2)tR=tR(F)=sup{t:R(t)2R}(reliablespan);(3)M=M(F)=/ootdF(t)(averagelife).]0Inreliabilityengineeringoneofthemostimportanttasksistoestimatethesereliabilityparameters,especiallytogivegoodlowerconfidencelimitsforthem.Whenitemsofsuchaproductareputintoareliabilitytestitoftenhappensthatnofailureismet.Example…     

极值理论(EVT)方法用于受险价值(VaR)计算的实证比较与分析

讨论了根据极值理论 ( EVT)计算受险价值 ( Va R)的两类不同的方法 :基于矩估计的“两次子样试算法”和极大似然估计法 ,并给出了各自理论推导过程和计算步骤 .同时 ,把这两类方法与正态分布和经验分布的结果进行了比较 .应用四种汇率历史数据进行的实证计算表明 ,在极端条件下 ,用极值理论方法估计 Va R具有很高的准确性 ,而矩估计法的结果又优于极大似然估计法 .     

噪声中弱相参脉冲列信号的一种检测方法

本文首先建立了一种广义的局部最优检测器(LOD)模型和准则,据此导出了一种窄带非Gauss噪声中确知相位相参脉冲序列弱信号的局部最优检测方法,采用Pitman的渐近相对效率(ARE)作指标研究了这一LOD的渐近性能,在Weibull和对数正态分布的噪声模型中对上述LOD的ARE作数值计算,从而获得一些有意义的结论。