首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到20条相似文献,搜索用时 351 毫秒
1.
本文研究具有均匀结构的多元$t$\,-模型的局部影响分析问题\bd 依据Cook的曲率度量, 我们考虑了微小扰动对统计推断的影响, 由此导出了局部影响分析中最为关心的统计量---最大曲率方向\bd作为一种应用, 本文还祥细讨论了常见的协方差加权扰动形式.  相似文献   

2.
本文较为详细地介绍了稳定分布的一些基本性质, 并通过股票指数收益率的稳定化PP图和直方图发现其具有高峰厚尾特征\bd 统计分析表明, 用稳定分布去刻画收益率分布的比其它分布更加有效\bd 最后介绍了稳定分布在金融风险度量应用中的有效性.  相似文献   

3.
区间数据任意阶原点矩的估计   总被引:1,自引:0,他引:1       下载免费PDF全文
在生存分析和可靠性研究中, 区间数据的存在常常使得传统的统计方法无法直接使用\bd 本文从无偏转换的思想出发, 对区间数据的任意阶原点矩进行了估计\bd 当截断变量的分布密度函数已知时, 得到了一批具有强相合性(收敛速度可以达到$n^{-1/2}(\log\log n)^{1/2}$)和渐近正态性的估计量, 并通过模拟计算对这种估计方法的可行性和有效性进行了验证.  相似文献   

4.
冯予 《应用概率统计》2006,22(4):365-380
对指数族非线性混合效应模型, 本文基于$Q$函数(朱宏图, 2001)方法, 给出几种度量数据删除影响的统计量\bd 其主要思想是将随机效应视为缺失数据, 并利用EM算法来处理完全数据对数似然函数的条件期望\bd 一个实际例子说明我们方法是有效的  相似文献   

5.
本文针对索赔次数数据的特点, 讨论了两类可导致散度偏大特征数据的分布类型: 零点膨胀分布与膨胀参数分布, 并根据Bayes理论与MCMC方法, 利用WinBUGS对其进行建模和抽样\bd 经过比较,给出了实现分布拟合的途径, 最后通过两个数值例子加以展示.  相似文献   

6.
价值风险(VaR)模型是当今最流行的金融资产风险管理和控制的工具之一\bd 本文提出了用局部分位数回归的方法来估计某一投资组合的VaR值\bd 该方法可用于计算投资组合多持续期的VaR, 使得人们可以了解到该投资组合在一定持续期内的动态风险\bd 本文通过模拟和美国三个月到期国债利率数据的分析说明了该方法的具体执行情况, 并与J.P. Morgan的时间开方规则作了比较\bd 结果表明我们的VaR估计有令人满意的效果.  相似文献   

7.
本文讨论了尺度参数模型参数变点的假设检验问题\bd 基于两样本$U$\,-统计量, 我们给出了两个检验, 并且研究了检验统计量分布的极限性质\bd 我们证明了这两个检验统计量的极限分布分别是$\sup\limits_{0相似文献   

8.
区间数据参数估计的叠代法   总被引:1,自引:0,他引:1       下载免费PDF全文
本文讨论区间数据情况下, 指数分布参数的估计\bd 引入了两种叠代方法, 证明了在一定的条件下, 叠代过程的收敛性.  相似文献   

9.
设$X_1,X_2,\cdots$为一列独立同分布的随机变量序列\bd 邵(1997)在没有任何矩条件下建立了自正则化大偏差定理, 但其上界的证明相当复杂\bd 为此, 本文给出了一个简洁的证明  相似文献   

10.
在经典的风险理论中涉及到的索赔风险是服从复合Poission过程的, 与之不同, 我们考虑Erlang(2)风险过程\bd Erlang(2)分布往往见诸于控制理论中, 这里它作为索赔发生间隔时间的分布被引入了\bd 本文中, 我们介绍一个与破产时刻、破产前时刻的盈余以及破产时刻赤字有关的辅助函数$\phi(\cdot)$, 函数中涉及的这三个变量对风险模型的研究都是最基本也是最重要的\bdWillmot and Lin (1999)曾在古典连续时间风险模型之中研讨过这一函数\bd受Gerber and Shi(1997)及Willmot and Lin (2000)在古典模型下的研究过程的启发, 本文的一个重要结果就是找到破产前时刻的盈余以及破产时刻赤字的联合分布密度函数\bd 更得益于Gerber and Landry (1998)及Gerber and Shiu (1999)的思想, 我们应用以上的结果去寻求基础资产服从一定风险资产价格过程的美式看跌期权最优交易策略.  相似文献   

11.
Zhou (2010) introduced a multivariate Wilcoxon regression estimate which possesses some nice properties: computational ease, asymptotic normality and high efficiency. However, it is sensitive to the leverage points. To circumvent this problem, we propose a weighted multivariate Wilcoxon regression estimate. Under some regularity conditions, the asymptotic normality is established. We further study the robustness of the proposed estimate through the influence function. By properly choosing the weight functions, our results show that the corresponding estimate can have bounded influence function on both response and covariates.  相似文献   

12.
The multivariate probit model is very useful for analyzing correlated multivariate dichotomous data. Recently, this model has been generalized with a confirmatory factor analysis structure for accommodating more general covariance structure, and it is called the MPCFA model. The main purpose of this paper is to consider local influence analysis, which is a well-recognized important step of data analysis beyond the maximum likelihood estimation, of the MPCFA model. As the observed-data likelihood associated with the MPCFA model is intractable, the famous Cook's approach cannot be applied to achieve local influence measures. Hence, the local influence measures are developed via Zhu and Lee's [Local influence for incomplete data model, J. Roy. Statist. Soc. Ser. B 63 (2001) 111-126.] approach that is closely related to the EM algorithm. The diagnostic measures are derived from the conformal normal curvature of an appropriate function. The building blocks are computed via a sufficiently large random sample of the latent response strengths and latent variables that are generated by the Gibbs sampler. Some useful perturbation schemes are discussed. Results that are obtained from analyses of an artificial example and a real example are presented to illustrate the newly developed methodology.  相似文献   

13.
Consistent goodness-of-fit tests are proposed for symmetric and asymmetric multivariate Laplace distributions of arbitrary dimension. The test statistics are formulated following the Fourier-type approach of measuring the weighted discrepancy between the empirical and the theoretical characteristic function, and result in computationally convenient representations. For testing the symmetric Laplace distribution, and in the particular case of a Gaussian weight function, a limit value of these test statistics is obtained when this weight function approaches a Dirac delta function. Interestingly, this limit value is related to a couple of well-known measures of multivariate skewness. A Monte Carlo study is conducted in order to compare the new procedures with standard tests based on the empirical distribution function. A real data application is also included.  相似文献   

14.
ASSESSMENT OF LOCAL INFLUENCE IN MULTIVARIATE ANALYSIS   总被引:3,自引:0,他引:3  
ASSESSMENTOFLOCALINFLUENCEINMULTIVARIATEANALYSIS¥(石磊,王学仁)ShiLei;WangXueren(InstituteofAppliedMathematicsofYunnanProvinceDepar...  相似文献   

15.
基于EM算法和Laplace逼近, 本文给出了研究ZI (即含0较多的)纵向计数数据模型的影响分析方法. 为了识别含0较多的分组计数数据中的强影响点, 本文将ZI纵向数据模型中取值为0的数据赋予一定的权重; 而把随机效应看作缺失数据; 在此基础上引入EM算法, 从而应用完全数据对数似然函数的条件期望以及相应的$Q$距离函数进行影响分析; 并进一步应用Laplace逼近方法简化EM算法中的积分计算. 在此基础上, 基于数据删除模型和局部影响分析方法导出了适用于ZI纵向计数数据模型的诊断统计量. 本文也通过实际计数数据的例子验证了诊断统计量的有效性.  相似文献   

16.
On weighting of bivariate margins in pairwise likelihood   总被引:1,自引:0,他引:1  
Composite and pairwise likelihood methods have recently been increasingly used. For clustered data with varying cluster sizes, we study asymptotic relative efficiencies for various weighted pairwise likelihoods, with weight being a function of cluster size. For longitudinal data, we also study weighted pairwise likelihoods with weights that can depend on lag. Good choice of weights are needed to avoid the undesirable behavior of estimators with low efficiency. Some analytic results are obtained using the multivariate normal distribution. For clustered data, a practically good choice of weight is obtained after study of relative efficiencies for an exchangeable multivariate normal model; they are different from weights that had previously been suggested. For longitudinal data, there are advantages to only include bivariate margins of adjacent or nearly adjacent pairs in the weighted pairwise likelihood.  相似文献   

17.
基于犯罪过程的不确定性结构,融合多变量主成份分析与因子分析算法,分析了影响犯罪率的城市化率、失业率、客运量、人均GDP、城市基尼系数、农村基尼系数等多个相关变量因素,由MATLAB仿真建立了犯罪率的多元回归模型,并采用MINITAB数学软件对浙江省1988-2007二十年样本数据进行了实测,获取了影响犯罪率的潜在因子与方差贡献率,讨论了多元回归模型的统计检验及相对误差,解决了犯罪率各相关变量的权重分布及信息相互重叠问题.  相似文献   

18.
We propose a general nonparametric approach for testing hypotheses about the spectral density matrix of multivariate stationary time series based on estimating the integrated deviation from the null hypothesis. This approach covers many important examples from interrelation analysis such as tests for noncorrelation or partial noncorrelation. Based on a central limit theorem for integrated quadratic functionals of the spectral matrix, we derive asymptotic normality of a suitably standardized version of the test statistic under the null hypothesis and under fixed as well as under sequences of local alternatives. The results are extended to cover also parametric and semiparametric hypotheses about spectral density matrices, which includes as examples goodness-of-fit tests and tests for separability.  相似文献   

19.
The Tukey depth is an innovative concept in multivariate data analysis. It can be utilized to extend the univariate order concept and advantages to a multivariate setting. While it is still an open question as to whether the depth contours uniquely determine the underlying distribution, some positive answers have been provided. We extend these results to distributions with smooth depth contours, with elliptically symmetric distributions as special cases. The key ingredient of our proofs is the well-known Cramér-Wold theorem.  相似文献   

20.
Single-index model is a potentially tool for multivariate nonparametric regression, generalizes both the generalized linear models(GLM) and the missing-link function problem in GLM. In this paper, we extend Cook’s local influence analysis to the penalized Gaussian likelihood estimator based on P-spline for the partially linear single-index model. Some influence measures, based on the minor perturbation of the model, are derived for the penalized least squares estimation. An illustrative example is also presented.  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号