多元回归模型中最大值点的BRPA估计的收敛速度

BRPA估计是Changchien(1990)提出的一种具有良好性质的回归函数最大值点的估计,Chen,Huang and Huang(1996),Bai and Huang(1999),吴and王(2000)和Bai,Chen and Wu(2003)分别讨论了BRPA的极限性质.本篇文章中,我们在很一般的条件下研究了z为多维向量时BRPA估计的收敛速度,推广了Bai,Chen and Wu(2003)的结果.     

一个两参数有浴盆形状失效率的寿命分布的参数估计

讨论了一个由Chen(2000)提出的两参数有浴盆形状失效率的寿命分布基于定数截尾样本的参数估计,导出了有关参数的逆矩估计量和参数的区间估计,并利用模拟方法研究了所给点估计的精度.还指出了Wu等(2005)提出的选择区间估计的最优准则是错误的.最后用一个实例说明本文所给的方法.     

第十六卷总目录

学术论文 一类隐函数及其在计量抽样检查中的应用汪仁官(1) 带有不完全信息随机截尾试验下Weibull分布参数的MLE的相合性 及渐近正态性杨纪龙叶尔骅(9) 两个未知均值方差混合模型有限制下对数极大似然比的极限分布(英) 成平(20) 矩阵损失下一类相依回归模型中的线性容许估计和Minimax估计李新民徐兴忠秦前清(25) 关于一般马氏过程遍历性的一个注记董召巩馥洲(31) 一类相依回归方程限定两步估计的有限样本结果陈永明(36) 基于负相协样本的经验过程的弱收敛(英) 袁明苏淳(45) 非时齐向量值马氏决策模型秦叔明张升(57) 指数型产品失效率鉴定试验的Bayes方案张志华姜礼平(66) 错误先验假定下回归系数Bayes估计的小样本性质韦来生(71) 期权价格函数的局部多项式估计茆诗松刘忠(81) 结构可靠性的精确置信下限郑忠国卜红军等(89) 集值序上鞅的若干有关问题(英) 汪荣明吴伟志(98) L-统计量的Edgeworth展开和Bootstrap逼近任哲陈明华(113) 更新理论积分方程的解析解康志荣闫玉斌(125) 随机变量的负超可加相依及其应用(英) 胡太忠(133) 增长曲线模型中向量函数的线性可容许性李俊海徐兴忠陈峥(145) 超布朗运动关于区域的首中方式(英) 唐加山赵学雷(152) 有限混合模型有限制Log极大似然比统计量的极限分布(英) 陈家骅成平(159) 关于超过程的几个比较定理(英) 张新生(168) 椭球等高分布的逆问题胡端平(177) 股票价格过程方差函数的统计推断肖庆宪郑祖康(182) 系统风险Beta系数的非参数估计顾娟茆诗松(191) 基于负相协样本经验过程的加权弱收敛(英) 袁明苏淳(199) 无RNP Banach空间中集值测度的Radon-Nikodym定理(英) 吴伟志张文修(208) 关于测验等值几个问题的研究陈希镇(213) 回归函数的投影寻踪逼近的Lp收敛性田铮肖华勇(225) 未知方向密度估计的收敛率(英) 崔恒建(229) 对数正态分布场合无失效的BAYES验证试验方案何基报茆诗松(239) 受约束的组合投资模型研究—最终财富效用优化费为银(249) 可变样本容量的质量控制图张维铭(255) 污染数据回归分析中参数的最小一乘估计任哲陈明华(262) 极限相对对数似然比与一类强偏差定理刘文(269) 不完全椭球约束下多指标线性模型中的可容许线性估计杨国庆(277) 倒向随机微分方程解的Malliavin微分林清泉(285) 马氏环境中马氏链的Shannon-McMillan-Breiman定理方大凡(295) 多元回归函数最大值点BRPA估计的相合性吴耀华王小明(299) 有交易费时的欧式期权定价刘道百(303) 一种多级评分模型及参数估计余军周纪芗(318) 求参数置信限的一种方法孙万龙(337) IRT多级评分项目的参数估计及其在测验中的应用杜文久(350) SV模型下的期权定价和风险计量刘忠(365) Lagrange方法和期权定价李小军(373) 截尾样本下回归函数改良核估计的强相合性胡玉萍薛留根(379) 上海市老年护理互助会会员会费交付平衡研究吴贤毅王静龙(391) 几种基于CAPM的最优投资组合构造方案及其比较何基报茆诗松(398) 拟正则保正型过份函数的积分表示及h-结合过程的轨道性质陈传钟(409) 非对称广义自回归条件异方差的新模型吴硕思方兆本(416) Hilbert-值半鞅序列的弱收敛(英) 李亮坤彭运佳谢颖超(423) 线性等值公式的误差估计陈希镇(435) 应用简报 肥胖教职工患心血管病情况的调查和分析徐进李桂枝(220) 多元统计分析在棉铃虫分级预报中的应用丁世飞325) 我国农作物受灾及成灾面积的综合预测分析陈平达庆利(329) 用回归分析比较两图书馆流通书库工作量李小梅陆俊陈恒芬(333) 学术活动报道 第十二届全国多指标随机过程学术讨论会 (223) 江苏省概率统计分会学术活动报导 (336) 上海财经大学召开统计学专业素质教育研讨会 (447) 戴世光教授在京逝世 (224) 第十五卷总目录 (109) Contents of Vol. 16 Articles An Implicit Functions and Its Applications for Variables Sampling Inspections Wang Renguan (1) Consistency and Asymptotic Normality of MLE of the Parameters of Weibull Distribution for Random Censoring Model with Incomplete Information Yang Jilong and Ye Erhua (9) The Limit Distribution of the Restricted Log Maximum Likelihood Ratio for Mixturc Models of Two Normal Distributions with Unknown Mean and Variance Cheng Ping (20) The Linear Admissible and Minimax Estimators in Seemingly Unrelated Regression Model under Matrix Loss Li Xinmin, Xu Xingzhong and Qin Qianqing (25) A Note for Ergodicity of General Markov Processes Dong Zhao and Gong Fuzhou (31) Some Exact Finite Sample Results of Estimators Based on Restricted Residuals in A Class of Seemingly Unrelated Regressions Chen Yongming (36) Weak Convergence for Empirical Processes of Negatively Associated Sequences Yuan Ming and Su Chun (45) A Non-stationa ry Discounted Vector-valued Markovian Decision Model with Unbounded Reward Qin Shuming and Zhang Sheng (57) A Bayesian Plan of Testing for Production Acceptence in Exponential Case Zhang Zhihua and Jiang Liping (66) The Small-sample Properties for the Bayes Estimator of Regression Coefficients under Misspecified Prior Assumption Wei Laisheng (71) Local Polynominal Estimation of Option-trading Function Mao Shisong and Liu Zhong (81) The Accurate Lower Confidence Limit for the Reliability of Structural System Zheng Zhongguo and Bu Hongjun et al. (89) Some Related Problems of SVO Supermartingales Wang Rongming and Wu Weizhi (98) On the Edgeworth Expansion and the Bootstrap Approximation for a L-statistic Ren Zhe and Chen Minghua (113) The Analytic Solution of the Integral Equation of the Renewal Theory Kang Zhirong and Yan Yubin (125) Negatively Superadditive Dependence of Random Variables with Applications TaiZhong Hu (133) Linear Admissibility of Vector Function in Growth Curve Model Li Junhai , Xu Xingzhong and Chen Zheng (145) The First Hitting Manner of Super-Brownian Motions Tang Jiashan and Zhao Xuelei (152) The Limiting Distribution of the Restricted Likelihood Ratio Statistic for Finite Mixture Models Chen Jiahua and Cheng Ping (159) On Comparison Theorems for Dawson-Watanabe Superprocesses Zhang Xinsheng (168) The Inverse Question of Elliptically Contoured Distribution Duanping Hu (177) The Ifference of the Variance Function of a Stock Price Process Xiao Qingxian and Zheng Zukang (182) The Nonparametric Estimation of the Systemetic Risk (Beta Coefficient) Gu Juan and Mao Shisong (191) Weighted Weak Convergence for Empirical Processes of Negatively Associated Sequences Yuan Ming and Su Chun (199) Radon-Nikodym Theorems for Set-valued Measures in Banach Space without RNP Wu Weizhi and Zhang Wenxiu (208) Reseaches on Several Problems about Test Equating Chen Xizhen (213) The Lp Convergence for Projection Pursuit Regression Tian Zheng and Xiao Huayong (225) Rate of Convergence of the Density Estimator on an Unknown Orientation Cui Hengjian (229) A Bayesian Zero-Failure Reliability Demonstraion Testing Procedure for Lognormal Distribution Jibao He and Shisong Mao (239) Study of Constrained Portfolio Model on Optimization of Utility from Terminal Wealth Fei Weiyin (249) Quality Control Charts with Variable Sample Size Zhang Weiming (255) Least Absolute Deviation Estimator of Parameter in Regression Analysis for Contamination Data Ren Zhe and Chen Minghua (262) Limit Relative Log-likelihood Ratio and a Class of Strong Deviation Theorems Liu Wen (269) Admissible Linear Estimation in a Multivariate Linear Model with Respect to an Incomplete Ellipsoidal Restriction Yang Guoqing (277) Malliavin Derivatives of Solutions for BSDE Lin Qingquan (285) Shannon-McMillan-Breiman Theorem for Markov Chains in Markovian Environments Da fan Fang (295) The Consistency of BRPA Estimator for the Maximizer of a Multivariable Regression Function Wu Yaohua and Wang Xiaoming (299) European Option Pricing with Transaction Costs Liu Daobai (303) A Polychotomously-Scored Responses Model and Parameter Estimation Yu Jun and Zhou Jixiang (318) A General Way for Obtaining Confidence Limits Sun Wanlong (337) Parameters Estimation of IRT Multicategory Scoring Item Du Wenjiu (350) Using SV Model to Price Option and Measure its Risk Liu Zhong (365) The Lagrange Method and Option Pricing Li Xiaojun (373) Strong Consistency of Improved Kernel Estimate of Regression Function with Censored Data Hu Yuping and Xue LiugenLiu Zhong (379) Calculating the Membership Due of the Aged-Care Fraternity Wu Xianyi and Wang Jinglong (391) Several Procedures for Determining Optimal Portfolio Based on CAPM with Comparision He Jibao and Mao Shisong (398) Representation of Excessive Functions and Some Path Properties of h-associated Processes of Quasi-regular Positivity Preserving Coercive Forms Chen Chuanzhong (409) A New Model for Asymmetric General Autoregressive Conditional heteroscedasticity Wu Shuosi and Fang Zhaoben (416) Weak Convergence of Hilbert-valued Semimartingale Sequence Leong-kwan Li and Wan-Kai Pang and Yingchao Xie (423) Estimation of Standard Errors about Linear Equating Chen Xizhen (435)     

误差为NOD线性模型参数M估计的强相合性

研究了随机误差为NOD序列的线性模型中回归参数β_0的M估计,在较弱的矩条件下证明了回归参数M估计的强相合性,推广和改进了陈和赵(1996),杨(2002)和Wu(2006)等的结果,推广了肖(2007)等的结果.     

On a Pair of Geometric Parameters of Orlicz Norm

Let be a pair of complementary N--funCtions, where gh and op are the right deriVatives of. andW respectively Defineandas in Wull1. Clearly, 1 5 Q. 5 oo for every .(u). Wangl'j and Wu, Chen and Wangl']showed that. E V2(0) if and only if Q. < oo and. E A2(0) if and ouly if q. > l. for andRenl4] utilized the parameter Q. when they Offered the fonwig esthoation of KOttmanconstants of the Orlicz sequence space l. equlpped with Orlicz norm:whereChen showed that (see [5, p.211)wherefor and …     

Meromorphic Function Sharing Sets with Its Difference Operator or Shifts

Let f be a nonconstant meromorphic function, c ∈ C, and let ■be a meromorphic function. If f(z) and P(z, f(z)) share the sets {a(z),-a(z)},{0} CM almost and share {∞} IM almost, where P(z, f(z)) is defined as(1.1), then f(z) ≡±P(z, f(z)) or f(z)P(z, f(z)) ≡±a~2(z). This extends the results due to Chen and Chen(2013), Liu(2009) and Yi(1987).     

MQ拟插值求解KdV方程

Quasi-interpolation is very useful in the study of approximation theory and its applications,since it can yield solutions directly without the need to solve any linear system of equations.Based on the good performance,Chen and Wu presented a kind of multiquadric （MQ） quasi-interpolation,which is generalized from the L D operator,and used it to solve hyperbolic conservation laws and Burgers’ equation.In this paper,a numerical scheme is presented based on Chen and Wu’s method for solving the Korteweg-de Vries （KdV） equation.The presented scheme is obtained by using the second-order central divided difference of the spatial derivative to approximate the third-order spatial derivative,and the forward divided difference to approximate the temporal derivative,where the spatial derivative is approximated by the derivative of the generalized L D quasi-interpolation operator.The algorithm is very simple and easy to implement and the numerical experiments show that it is feasible and valid.     

APPROXIMATING SOLUTION OF 0∈ T（x） FOR AN H-MONOTONE OPERATOR IN HILBERT SPACES

The purpose of this paper is to study the solution of 0 ∈ T (x) for an H-monotone operator introduced in [Fang and Huang, Appl. Math. Comput. 145(2003)795-803] in Hilbert spaces, which is the first pro...     

利用完全辅助信息的模型校正信息论方法 (英)

本文我们提出了使用调查数据中完全辅助信息的模型校正K-L相对熵最小化方法．在估计有限总体均值时我们的估计渐近等价于MC估计(Wu and Sitter(2001))．我们方法一个有吸引力的优点是,导出的权具有特征:pi>0和■pi=0 ．这使得可把此方法应用于估计分布函数和分位数．导出的分布函数估计量FMKL(y)渐近等价于广义回归估计,且本身是一分函数布．     

ANNALS OF DIFFERENTIAL EQUATIONS Contents of Volume 19

Numberl(l)An Instability Theorem for A Certain Seventh一order Differential Equation ..……,. ...........................……,..........……,...........……A.ISADEKExistenee and Attraetiviof Almost Periodie Solution for HoPfield Neural Networksstenee and Attraetlvlty ofWith Variable Coeffieients·····……Chen Anping(6)g子alhen&Huang Lihong(19)Equations·,’·井几二;二;·少a砰.Yol玛理i,乃a只Peng&Ya’ly rerLurDeQ几eacLlon Ulflllsloll乙ystemSn Jurang(24)、1,声、.,了、l声、、月J…     

Convergence rate of the best-r-point-average estimator for the maximizer of a nonparametric regression function

The best-r-point-average (BRPA) estimator of the maximizer of a regression function, proposed in Changchien (in: M.T. Chao, P.E. Cheng (Eds.), Proceedings of the 1990 Taipei Symposium in Statistics, June 28–30, 1990, pp. 63–78) has certain merits over the estimators derived through the estimation of the regression function. Some of the properties of the BRPA estimator have been studied in Chen et al. (J. Multivariate Anal. 57 (1996) 191) and Bai and Huang (Sankhya: Indian J. Statist. Ser. A. 61 (Pt. 2) (1999) 208–217). In this article, we further study the properties of the BRPA estimator and give its convergence rate under some quite general conditions. Simulation results are presented for the illustration of the convergence rate. Some comparisons with existing estimators such as the Müller estimator are provided.     

Finite and infinite time interval BSDEs with non-Lipschitz coefficients

This paper aims at solving multidimensional backward stochastic differential equations (BSDEs) under weaker assumptions on the coefficients, considering both a finite and an infinite time interval. We establish a general existence and uniqueness result of the solutions to finite and infinite time interval BSDEs with non-Lipschitz coefficients, which generalizes the corresponding results in Mao (1995), Wang and Wang (2003), Wang and Huang (2009), Chen (1997) and Chen and Wang (2000).     

High breakdown estimators for principal components: the projection-pursuit approach revisited

Li and Chen (J. Amer. Statist. Assoc. 80 (1985) 759) proposed a method for principal components using projection-pursuit techniques. In classical principal components one searches for directions with maximal variance, and their approach consists of replacing this variance by a robust scale measure. Li and Chen showed that this estimator is consistent, qualitative robust and inherits the breakdown point of the robust scale estimator. We complete their study by deriving the influence function of the estimators for the eigenvectors, eigenvalues and the associated dispersion matrix. Corresponding Gaussian efficiencies are presented as well. Asymptotic normality of the estimators has been treated in a paper of Cui et al. (Biometrika 90 (2003) 953), complementing the results of this paper. Furthermore, a simple explicit version of the projection-pursuit based estimator is proposed and shown to be fast to compute, orthogonally equivariant, and having the maximal finite-sample breakdown point property. We will illustrate the method with a real data example.     

A non-interior continuation method for second-order cone programming

We extend the smoothing function proposed by Huang, Han and Chen [Journal of Optimization Theory and Applications, 117 (2003), pp. 39–68] for the non-linear complementarity problems to the second-order cone programming (SOCP). Based on this smoothing function, a non-interior continuation method is presented for solving the SOCP. The proposed algorithm solves only one linear system of equations and performs only one line search at each iteration. It is shown that our algorithm is globally and locally superlinearly convergent in absence of strict complementarity at the optimal solution. Numerical results indicate the effectiveness of the algorithm.     

On the accelerated modified Newton-HSS method for systems of nonlinear equations

Hermitian and skew-Hermitian splitting (HSS) method converges unconditionally, which is efficient and robust for solving non-Hermitian positive-definite systems of linear equations. For solving systems of nonlinear equations with non-Hermitian positive-definite Jacobian matrices, Bai and Guo proposed the Newton-HSS method and gave numerical comparisons to show that the Newton-HSS method is superior to the Newton-USOR, the Newton-GMRES and the Newton-GCG methods. Recently, Wu and Chen proposed the modified Newton-HSS (MN-HSS) method which outperformed the Newton-HSS method. In this paper, we will establish a new accelerated modified Newton-HSS (AMN-HSS) method and give the local convergence theorem. Moreover, numerical results show that the AMN-HSS method outperforms the MN-HSS method.     

Nonlinear least-squares estimation

The paper uses empirical process techniques to study the asymptotics of the least-squares estimator (LSE) for the fitting of a nonlinear regression function. By combining and extending ideas of Wu and Van de Geer, it establishes new consistency and central limit theorems that hold under only second moment assumptions on the errors. An application to a delicate example of Wu's illustrates the use of the new theorems, leading to a normal approximation to the LSE with unusual logarithmic rescalings.     

Asymptotic efficient estimation in semiparametric nonlinear regression models

§１ＩｎｔｒｏｄｕｃｔｉｏｎＣｏｎｓｉｄｅｒｔｈｅｆｉｘｅｄｄｅｓｉｇｎｓｅｍｉｐａｒａｍｅｔｒｉｃｎｏｎｌｉｎｅａｒｒｅｇｒｅｓｓｉｏｎｍｏｄｅｌｓｇｉｖｅｎｂｙｙｉ＝ｆ（ｘｉ,θ）＋λ（ｔｉ）＋εｉ,ｉ＝１,．．．,ｎ,（１）ｗｈｅｒｅｆ（,）ｉ...     

Bootstrap approximation of tail dependence function

For estimating a rare event via the multivariate extreme value theory, the so-called tail dependence function has to be investigated (see [L. de Haan, J. de Ronde, Sea and wind: Multivariate extremes at work, Extremes 1 (1998) 7-45]). A simple, but effective estimator for the tail dependence function is the tail empirical distribution function, see [X. Huang, Statistics of Bivariate Extreme Values, Ph.D. Thesis, Tinbergen Institute Research Series, 1992] or [R. Schmidt, U. Stadtmüller, Nonparametric estimation of tail dependence, Scand. J. Stat. 33 (2006) 307-335]. In this paper, we first derive a bootstrap approximation for a tail dependence function with an approximation rate via the construction approach developed by [K. Chen, S.H. Lo, On a mapping approach to investigating the bootstrap accuracy, Probab. Theory Relat. Fields 107 (1997) 197-217], and then apply it to construct a confidence band for the tail dependence function. A simulation study is conducted to assess the accuracy of the bootstrap approach.     

New modulus-based matrix splitting methods for implicit complementarity problem

Numerical Algorithms - In this paper, based on the published works by Bai and Tong (J. Univ. Electr. Sci. Tech. China 22:420–424, 1993) and Bai and Huang (J. Univ. Electr. Sci. Tech. China...