���й̶�ЧӦ�İ�����������ģ�͵Ļع���������

In this paper, we study the asymptotic behavior of the B-spline estimator for semiparametric panel data model with fixed effects.We give explicit expression for the asymptotic bias of B-spline estimator for nonparametric function m. Our study shows that the asymptotic bias of the B-spline estimator does not depend on the working correlation matrix. Simulations are conducted to demonstrate our conclusion.     

�ܸ�ЧӦ�����һ���·���

??Leverage effect often arises in many fields,such as financial risk management, portfolio and option pricing. However,it still remains to be studied that whether there is leverage effect or not in real data. Based on local polynomial regression estimation and Kolmogorov-Smirnov nonparametric test, this paper introduces a new nonparametric test statistic for the leverage effect, and some asymptotic properties are also presented. Simulation studies show that the proposed method performs well. Finally, empirical studies on SP500 index and Microsoft data imply that leverage effect exists in the real data, which is consistent with the idea in finance.     

���ЧӦģ���з��������Bayes���Ƽ���������

??The Bayes estimators of variance components are derived underweighted square loss function for the balanced one-way classification random effectsmodel with the assumption that variance component has the conjugate prior distribution.The superiorities of the Bayes estimators for variance components to traditional ANOVAestimators are studied in terms of the mean square error (MSE) criterion. Finally, aremark for main results is given.     

�̶�ЧӦ������ݲ�������ģ�͵ļ�Ȩ����LSDV����

This paper concerns with the estimation of a fixed effects panel data partially linear regression model with the idiosyncratic errors being an autoregressive process. For fixed effects short time series panel data, the commonly used autoregressive error structure fitting method will not result in a consistent estimator of the autoregressive coefficients. Here we propose an alternative estimation and show that the resulting estimator of the autoregressive coefficients is consistent and this method is workable for any order autoregressive error structure. Moreover, combining the B-spline approximation, profile least squares dummy variable (PLSDV) technique and consistently estimated the autoregressive error structure, we develop a weighted PLSDV estimator for the parametric component and a weighted B-spline series (BS) estimator for the nonparametric component. The weighted PLSDV estimator is shown to be asymptotically normal and more asymptotically efficient than the one which ignores the error autoregressive structure. In addition, this paper derives the asymptotic bias of the weighted BS estimator and establish its asymptotic normality as well. Simulation studies and an example of application are conducted to illustrate the finite sample performance of the proposed procedures.     

�������Ի��ЧӦģ�͵���Ч����

In this paper an efficient estimation methodology for the partially linear models with random effects is proposed. For this, we use the generalized least square estimate (GLSE) and the B-splines methods to estimate the unknowns, and employ the penalized least square method to obtain the estimators of the random effects item. Further, we also consider the estimation for the variance components. Compared with the existing methods, our proposed methodology performs well. The asymptotic properties of the estimators are obtained. A simulation study is carried out to assess the performance of our proposed methodology.     

ʧЧ��������ϵͳ���������Ԫ������

??Coherent systems are very important in reliability,survival analysis and other life sciences. In this paper, we consider the number of working components in an $(n-k+1)$-out-of-$n$ system, given that at least $(n-m+1)$ components are working at time $t$, and the system has failed at time $t$. In this condition, we compute the probability that there are exactly $i$ working components. First the reliability and several stochastic properties are obtained. Furthermore, we extend the results to general coherent systems with absolutely continuous and exchangeable components.     

������ݽ����̶�ЧӦģ�͵�Э����������

??In this paper, we focus on the tests for covariance matrices in panel data model with interactive fixed effects. For the problem of testing identity and sphericity of covariance matrices, we first propose test statistics based on the estimators of the trace of covariance matrices. Under both the null hypothesis and the alternatives, we establish the asymptotic distributions of the proposed test statistics under some regularity conditions, and we further show that the proposed tests are distribution free. Subsequently simulation studies suggest that the proposed tests perform well under the high dimensional panel data.     

��ƽ��ND���в��ֺ͵ľ�ȷ������

In this paper, by using central limit theorem of ND sequences and probability inequality, the precise asymptotics for partial sums of nonstationary ND sequences is investigated, and the same results with it under that of NA sequences are obtained.     

���������ع�ģ���з�������ľ�ȷ����

本文利用广义p-值和广义置信区间的概念构造 含有三个随机效应的套误差分量模型中方差分量的几种新的精确检验和置信区间, 并讨论它们在尺度变换下的不变性. 模拟结果表明, 基于广义p-值的检验很好地控制了犯第一类错误的概率.     

指数族广义非线性随机系数模型的变离差检验

指数族广义非线性随机系数模型是Smith &; Heitjan［１０］和 Wei et al［１１］所研究模型的推广。该文分别在模型离差 (dispersion) 的权不变和变异时，讨论了指数族 广义非线性随机系数模型的变离差的检验问题，得到了score检验统计量。并利用欧洲野兔数据，分别对正态分布模型、Γ 分布模型和 逆高斯分布模型说明检验方法的有效性。     

Generalized Nonparametric Mixed Effects Models

Generalized linear mixed effects models (GLMM) provide useful tools for correlated and/or over-dispersed non-Gaussian data. This article considers generalized nonparametric mixed effects models (GNMM), which relax the rigid linear assumption on the conditional predictor in a GLMM. We use smoothing splines to model fixed effects. The random effects are general and may also contain stochastic processes corresponding to smoothing splines. We show how to construct smoothing spline ANOVA (SS ANOVA) decompositions for the predictor function. Components in a SS ANOVA decomposition have nice interpretations as main effects and interactions. Experimental design considerations help determine which components are fixed or random. We estimate all parameters and spline functions using stochastic approximation with Markov chain Monte Carlo (MCMC). As iteration increases we increase the MCMC sample size and decrease the step-size of the parameter update. This approach guarantees convergence of the estimates to the expected fixed points. We evaluate our methods through a simulation study.     

基于M估计的线性混合效应模型中方差的齐性检验

本文对纵向数据的线性混合模型,用Fisher得分法得到了参数的M估计(稳健估计),给出了其渐近性质,研究了M估计下异方差的Score检验问题,并对检验统计量的功效进行了模拟,最后通过葡萄糖数据的实例说明了本文方法的有效性.     

随机环境中广义随机游动的灭绝概率

随机环境中广义随机游动(GRWRE)是随机环境中随机游动(RWRE)的推广．该文构造了非负整数集上的GRWRE,证明了这种模型的存在性,并计算了灭绝概率．     

不平衡单因素随机模型在职业接触评价中的应用

在职业接触评价中,单因素随机模型可用于评价工人接触均值超过职业接触限值的概率.当数据不平衡时, 本文利用广义推断研究了关于此概率的假设检验,并对此方法与已有方法进行了模拟对比研究. 模拟结果表明,本文所给方法优于已有方法, 特别是在数据极不平衡时效果更优.     

离散型广义非线性纵向数据模型中偏离名义离差的检验及其功效模拟

离散型广义非线性模型包括Poisson,二项,负二项模型.本文讨论离散型广义非线性纵向数据模型中偏离名义离差的检验问题,得到了检验的score统计量,并利用MonteCarlo方法研究了检验统计量的性质.最后,利用杀虫剂数据说明了检验方法的应用.     

随机凝聚型广义内向映射的随机不动点指数

本文引进了随机广义内向映射的随机不动点指数，利用该不动点指数我们得到了一些新的随机不动点定理，并给出了其一个应用．     

Fractional Generalized Random Fields of Variable Order

Abstract

We study the class of random fields having their reproducing kernel Hilbert space isomorphic to a fractional Sobolev space of variable order on ? ⁿ . Prototypes of this class include multifractional Brownian motion, multifractional free Markov fields, and multifractional Riesz–Bessel motion. The study is carried out using the theory of generalized random fields defined on fractional Sobolev spaces of variable order. Specifically, we consider the class of generalized random fields satisfying a pseudoduality condition of variable order. The factorization of the covariance operator of the pseudodual allows the definition of a white-noise linear filter representation of variable order. In the ordinary case, the Hölder continuity, in the mean-square sense, of the class of random fields introduced is proved, and its mean-square Hölder spectrum is defined in terms of the variable regularity order of the functions in the associated reproducing kernel Hilbert space. The pseudodifferential representation of variable order of the resulting class of multifractal random fields is also defined. Some examples of pseudodifferential models of variable order are then given.     

基于纵向数据的Poisson-Gamma模型系数的随机性检验

应用随机系数化方法对纵向数据的Poisson-Gamma回归模型进行了研究,采用Laplace展开方法得到了关于响应变量的近似似然函数并得到模型系数的随机性检验的Score统计量.通过Monte Carlo模拟分析了检验的渐近功效.最后把得到的检验统计量应用到具体的数值实例分析中说明其有效性.     

随机贴现因子下的纯保费精算

在贴现因子为随机的条件下,给出终身寿险纯保费的精算公式.