多维广义自回归条件异方差模型

In this paper,by making use of the Hadamard product of matrices,a natural and reasonable generalization of the univariate GARCH(Generalized Autoregressive Conditional heteroscedastic)process introduced by Bollerslev(J.Econometrics 31(1986),307-327)to the multivariate case is proposed.The conditions for the existence of strictly stationary and ergodic solutions and the existence of higher order moments for this class of parametric models are derived.     

Degeneracy in Heteroscedastic Regression Models

The maximum likelihood estimation in a regression model with heteroscedastic errors is considered. When the design matrices in the model are inappropriately specified, the maximum likelihood estimates of the variances of certain observations are found to be zero irrespective of the observed values, resulting in degeneracy. Necessary and sufficient conditions for degeneracy are given and used for its avoidance.     

多元线性模型中条件最优预测的稳健性

研究了多元线性模型中条件最优线性无偏预测的稳健性问题,得到了条件线性可预测变量的这种预测关于协方差矩阵具有稳健性的充要条件.     

Confidence Intervals of Variance Functions in Generalized Linear Model

In this paper we introduce an appealing nonparametric method for estimating variance and conditional variance functions in generalized linear models （GLMs）, when designs are fixed points and random variables respectively, Bias-corrected confidence bands are proposed for the （conditional） variance by local linear smoothers. Nonparametric techniques are developed in deriving the bias-corrected confidence intervals of the （conditional） variance. The asymptotic distribution of the proposed estimator is established and show that the bias-corrected confidence bands asymptotically have the correct coverage properties. A small simulation is performed when unknown regression parameter is estimated by nonparametric quasi-likelihood. The results are also applicable to nonparamctric autoregressive times series model with heteroscedastic conditional variance.     

广义超度量矩阵的封闭性质

本文研究了广义超度量矩阵的封闭性质.证明了若A为非奇异的广义超度量矩阵,则A与A的转置的Hadamard积仍然是一个广义超度量矩阵,并且它的逆矩阵是一个对角占优的M矩阵.给出了两个广义超度量矩阵Hadamard积封闭的一个充分条件.最后,讨论了广义超度量矩阵的Perron补与和的封闭条件.     

线性约束下异方差回归模型参数的极大似然估计

运用参数的极大似然估计法,给出在线性约束条件Hβ=C下异方差回归模型参数β和λ的极大似然估计,并讨论了估计参数的性质和模型的残差.利用得到的结论对线性约束下异方差回归模型的进一步研究和应用具有一定的理论和实际价值.     

Wavelet Estimation in Heteroscedastic Model Under Censored Samples

Consider the heteroscedastic regression model Yi = g（xi） ＋ σiei, 1 ≤ i ≤ n, where σi^2 = f（ui）, here （xi, ui） being fixed design points, g and f being unknown functions defined on [0, 1], ei being independent random errors with mean zero. Assuming that Yi are censored randomly and the censored distribution function is known or unknown, we discuss the rates of strong uniformly convergence for wavelet estimators of g and f, respectively. Also, the asymptotic normality for the wavelet estimators of g is investigated.     

���ڱ���ѡ��;�����������׶��췽��ģ�͹���

The heteroscedasticity is inevitable for the panel data modeling in economics. The two-stage estimation method is a better means to study the heteroscedasticity, in which the basis is to select only one independent variable for samples grouping, it can cause the information used is incomplete. In this paper, we propose to select several variables for grouping using variable selection method, then k-mean algorithm is used to cluster, so the samples classification can be achieved and the heteroscedasticity estimation can be obtained. The results of real example analysis show that the method presented in this paper has obvious advantages in effectiveness and feasibility.     

一个部份自回归模型的渐近有效性<英>

本文考虑部分自回归模型 X_t=X_(t-1)β g(U_t) ε_t,t≥1.这里g是一未知函数,β是一待估参数,ε_j是具有0均值和方差σ~2的i.i.d.误差,U_t i.i.d.服从[0,1]上均匀分布.本文首先给出了相合估计的收敛阶和Takeuchi意义下渐近有效界.同时给出了β最小二乘估计是有效的充要条件.最后证明了MLE是渐近有效的.     

�����췽��ģ����̫���ܵ���˻����ɿ��Է����е�Ӧ��

Solar cell is the basic component of satellite photovoltaic panels with complicated redundant system structure. Its reliability plays an important role in the system, and its performance shows a degradation trend over time. In this paper, study is conducted for the solar cell degradation modeling and reliability analysis basedon practical testing results. Specifically, we illustrate an accelerated test for the attenuation ratio character test under different accumulativeirradiation levels, focusing on the heteroscedasticity of the collected testing data. A heteroscedastic linear model is proposed, and the lifedistribution of the photovoltaic panel is obtained by using Fiducial method. A numerical example is shown for the purpose of illustration.     

Detecting and Diagnostic Checking Multivariate Conditional Heteroscedastic Time Series Models

Two tests for multivariate conditional heteroscedastic models are proposed. One is based on the cross-correlations of standardized squared residuals and the other is a score (Lagrange multiplier) test. The cross-correlations test can be used to detect the presence of multivariate conditional heteroscedasticity whereas the other test can be used for diagnostic checking. Simulation studies on the size and power of the test statistics are reported. The application of the tests is illustrated by an example using the S & P 500 and Sydney All Ordinary Indexes.     

���������Իع�ģ���лع麯���İ��������

??In this paper, semiparametric estimation of a regression function in the third order partially linear autoregressive model with first order autoregressive errors is mainly studied. We suppose that the regression function has a parametric framework, and use the conditional least squares method to obtain the parameter estimators. Then semiparametric estimators of the regression function can be given by combining with the nonparametric kernel function adjustment. Furthermore, under certain conditions, the consistency of the estimators is proved. Finally, simulation research is presented to evaluate the effectiveness of the proposed method.     

Tail Behavior of a Threshold Autoregressive Stochastic Volatility Model

We consider a threshold autoregressive stochastic volatility model where the driving noises are sequences of iid regularly random variables. We prove that both the right and the left tails of the marginal distribution of the log-volatility process (α_t)_t are regularly varying with tail exponent −α with α > 0. We also determine the exact values of the coefficients in the tail behaviour of the process (α_t)_t. AMS 2000 Subject Classification. Primary—62G32, 62PO5     

ARCH(p)模型样本均值与样本自相关函数的渐近正态性

利用严平稳m步相依序列中心极限定理证明了ARCH(p)模型样本均值与样本自相关函数的渐近正态性质.     

非线性自回归序列的矩的存在性

本文研究平稳非线性自回归序列的高阶矩的存在性问题,此序列满足带条件异方差的非线性自回归模型。其主要结果是：在某些平稳条件下,只要新息序列具有有穷的r(r≥1)阶矩,该模型的平稳解也有有穷的r阶矩。     

广义循环矩阵的一个性质

可表为非奇异对角矩阵和循环矩阵乘积的矩阵,我们称其为广义循环矩阵.本文给出了单位矩阵与广义循环矩阵的和矩阵的非奇异的充要条件,得到了这样和矩阵的相对增益阵列的显示表达式.     

Geometric Ergodicity of Metropolis-Hastings Algorithms for Conditional Simulation in Generalized Linear Mixed Models

Conditional simulation is useful in connection with inference and prediction for a generalized linear mixed model. We consider random walk Metropolis and Langevin-Hastings algorithms for simulating the random effects given the observed data, when the joint distribution of the unobserved random effects is multivariate Gaussian. In particular we study the desirable property of geometric ergodicity, which ensures the validity of central limit theorems for Monte Carlo estimates.     

Order Determination for Multivariate Autoregressive Processes Using Resampling Methods

LetX₁, …, X_nbe observations from a multivariate AR(p) model with unknown orderp. A resampling procedure is proposed for estimating the orderp. The classical criteria, such as AIC and BIC, estimate the orderpas the minimizer of the function[formula]wherenis the sample size,kis the order of the fitted model, Σ²_kis an estimate of the white noise covariance matrix, andC_nis a sequence of specified constants (for AIC,C_n=2m²/n, for Hannan and Quinn's modification of BIC,C_n=2m²(ln ln n)/n, wheremis the dimension of the data vector). A resampling scheme is proposed to estimate an improved penalty factorC_n. Conditional on the data, this procedure produces a consistent estimate ofp. Simulation results support the effectiveness of this procedure when compared with some of the traditional order selection criteria. Comments are also made on the use of Yule–Walker as opposed to conditional least squares estimations for order selection.     

半参数变系数异方差部分线性模型下的经验似然

Consider the semiparametric varying-coefficient heteroscedastic partially linear model Y i = Xτiβ + Zτiα(Ti) + σiei,1 ≤ i ≤ n,where σ 2 i = f(Ui),β is a p × 1 column vector of unknown parameter,(Xi,Zi,Ti,Ui) are random design points,Y i are the response variables,α(·) is a q-dimensional vector of unknown functions,e i are random errors.For both cases that f(·) is known and unknown,we propose the empirical log-likelihood ratio statistics for the parameter β.For each case,a nonparametric version of Wilks’ theorem is derived.The results are then used to construct confidence regions of the parameter.Simulation studies are carried out to assess the performance of the empirical likelihood method.     

常利率下自回归索赔模型的破产概率的界

研究常利率下的一个广义连续时间更新风险模型的(最终)破产概率,其中自回归过程模拟相依的索赔过程.通过更新的递推方法,得到了此模型破产概率的指数上、下界.