共查询到19条相似文献,搜索用时 375 毫秒
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方差和相关系数的齐性是纵向数据分析中常用假设之一,然而,这些假设未必合适.本文主要研究的是具有指数相关结构的纵向数据非线性混合效应模型,首先将Huber函数引入模型的对数似然函数中,利用Fisher得分迭代法得到模型参数的稳健估计(M估计),然后基于M估计对模型的方差和相关系数的齐性进行了Score检验,并给出了检验统计量的Monte-Carlo模拟结果.最后用一个实例说明了本文的方法. 相似文献
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林路 《数学的实践与认识》1997,(3)
本文首次研究线性模型中有偏估计的强影响点的显著性检验。通过后验分布对数似然函数,本文求出了检验岭估计、广义岭估计和Stein估计的强影响点的Score检验统计量,并用实例说明同一组数据对不同估计的影响的差异。 相似文献
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本文考虑变系数ARCH—M模型,构造了非参数部分和参数部分的截面似然估计。基于估计的渐近性质,构造了Wald检验统计量来检验模型是否具有条件异方差性。数值模拟结果表明,所构造的估计和Wald统计量具有良好的有限样本性质。 相似文献
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微观调查数据是微观数据的重要组成,微观调查数据的权数在最小二乘估计下的统计推断,已有多篇文献提出了不同的检验方法,但在最大似然估计下的统计推断,权数的检验还无明确的方法。依据常见的三种似然检验方法,本文给出了Wald权数检验、似然比权数检验和拉格朗日乘子权数检验,理论与模拟的结果发现,这三种似然权数检验均具有较高的犯第一类错误概率,本文利用Bartlett-type correction,获得修正得分权数检验,并从理论和模拟角度说明了获得的修正得分权数检验的优势,同时将这四种权数检验方法应用到中国家庭追踪调查(CFPS)数据,最后对该方法进行了总结和展望。 相似文献
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针对单指数投资组合模型,用稳健的M估计去估计模型参数,减少了样本数据异常值对模型的影响,并对沪市权重股进行了实证检验,得到了投资组合的有效前沿。 相似文献
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Sun Huihui 《应用概率统计》2013,29(5):469-479
In this paper, the Fisher scoring method
is applied to get M-estimator (robust estimator) in the mixed
effects linear model for longitudinal data. The score tests for
correlation coefficients in the model with uniform correlation
covariance structure based on M-estimator are also studied. Then the
properties of test statistics are investigated through Monte Carlo
simulations. At last, the methods and properties are illustrated by
the grape sugar data example. 相似文献
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This paper studies an M-estimator of a proxy periodic GARCH (p, q) scaling model and establishes its consistency and asymptotic normality. Simulation studies are carried out to assess the performance of the estimator. The numerical results show that our M-estimator is more efficient and robust than other estimators without the use of high-frequency data. 相似文献
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In this paper we introduce a family of symmetrised M-estimators of multivariate scatter. These are defined to be M-estimators only computed on pairwise differences of the observed multivariate data. Symmetrised Huber's M-estimator and Dümbgen's estimator serve as our examples. The influence functions of the symmetrised M-functionals are derived and the limiting distributions of the estimators are discussed in the multivariate elliptical case to consider the robustness and efficiency properties of estimators. The symmetrised M-estimators have the important independence property; they can therefore be used to find the independent components in the independent component analysis (ICA). 相似文献
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Acta Mathematicae Applicatae Sinica, English Series - This paper considers a nonparametric M-estimator of a regression function for functional stationary ergodic data. More precisely, in the... 相似文献
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Alexander J. Gibberd James D. B. Nelson 《Journal of computational and graphical statistics》2017,26(3):623-634
The time-evolving precision matrix of a piecewise-constant Gaussian graphical model encodes the dynamic conditional dependency structure of a multivariate time-series. Traditionally, graphical models are estimated under the assumption that data are drawn identically from a generating distribution. Introducing sparsity and sparse-difference inducing priors, we relax these assumptions and propose a novel regularized M-estimator to jointly estimate both the graph and changepoint structure. The resulting estimator possesses the ability to therefore favor sparse dependency structures and/or smoothly evolving graph structures, as required. Moreover, our approach extends current methods to allow estimation of changepoints that are grouped across multiple dependencies in a system. An efficient algorithm for estimating structure is proposed. We study the empirical recovery properties in a synthetic setting. The qualitative effect of grouped changepoint estimation is then demonstrated by applying the method on a genetic time-course dataset. Supplementary material for this article is available online. 相似文献
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We propose sieve M-estimator for a semi-functional linear model in which the scalar response is explained by a linear operator of functional predictor and smooth functions of some real-valued random variables.Spline estimators of the functional coefficient and the smooth functions are considered,and by selecting appropriate knot numbers the optimal convergence rate and the asymptotic normality can be obtained under some mild conditions.Some simulation results and a real data example are presented to illustrate the performance of our estimation method. 相似文献
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Jun Shao 《Annals of the Institute of Statistical Mathematics》1992,44(4):687-701
To estimate the dispersion of an M-estimator computed using Newton's iterative method, the jackknife method usually requires to repeat the iterative process n times, where n is the sample size. To simplify the computation, one-step jackknife estimators, which require no iteration, are proposed in this paper. Asymptotic properties of the one-step jackknife estimators are obtained under some regularity conditions in the i.i.d. case and in a linear or nonlinear model. All the one-step jackknife estimators are shown to be asymptotically equivalent and they are also asymptotically equivalent to the original jackknife estimator. Hence one may use a dispersion estimator whose computation is the simplest. Finite sample properties of several one-step jackknife estimators are examined in a simulation study.The research was supported by Natural Sciences and Engineering Research Council of Canada. 相似文献
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The Sign Covariance Matrix is an orthogonal equivariant estimator of multivariate scale. It is often used as an easy-to-compute and highly robust estimator. In this paper we propose a k-step version of the Sign Covariance Matrix, which improves its efficiency while keeping the maximal breakdown point. If k tends to infinity, Tyler’s M-estimator is obtained. It turns out that even for very low values of k, one gets almost the same efficiency as Tyler’s M-estimator. 相似文献