连续型半参数广义线性纵向数据模型的方差成分检验

回归模型的方差成分检验是一个非常重要的问题.该文针对离差参数的变异, 随机效应的影响及两者同时具有的三种情形, 研究了基于纵向数据的连续型半参数广义线性模型的方差成分检验, 得到了Score检验统计量, 最后通过计算机模拟验证了该文所提出的方法的有效性.     

半参数广义线性随机效应模型的影响分析

该文系统研究了半参数广义线性随机效应模型的统计诊断与影响分析方法, 证明了数据删除模型和均值漂移模型的等价性定理, 给出了广义Cook距离等诊断统计量及异常点的Score检验统计量并研究了该模型的局部影响分析,分别对加权扰动模型, 响应变量扰动模型得到了影响距阵的计算公式, 最后通过一个实例验证了文中给出诊断方法的有效性.     

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.     

基于连续可分的广义非线性纵向数据模型偏离名义离差的score检验及其功效

指数族非线性模型或广义非线性模型是广义线性模型和正态回归模型的自然推广.本文针对可分的连续型指数族回归模型(如正态模型,Γ模型,逆高斯模型),讨论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,并推导了它们的渐近分布和局部近似功效.然后利用Monte Carlo方法研究了检验统计量的性质.最后利用百慕大草地数据说明了检验方法的应用.     

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在广义参数和非参数模型中, 虽然不存在异方差检验问题, 但是方差成分的检验问题仍是研究者们关心的对象. 本文利用P-样条的方法, 研究了广义单指标混合模型的方差成分检验问题. 得到了检验广义单指标混合模型是否存在由随机效应引起的偏大离差问题的Score检验统计量, 最后给出计算机模拟的例子, 证实了文中所提出方法的可行性和有效性, 推广和发展了先前的研究工作     

一类相合的分位点型检验

广义非参数似然比检验统计量是一类很广的统计量,包含了众多重要的检验统计量,如Anderson-Darling(AD)等.利用Rubin的随机经验分布函数替代经验分布函数的方法,得到了广义非参数似然比检验统计量的新版本,构造了新的检验统计量.由于新的检验统计量在给定样本下仍然是随机变量,选择了它的分位点和期望作为检验统计量,分别称之为分位点型检验统计量和期望型检验统计量.在简单假设情况下,证明了分位点型检验统计量和期望型检验统计量在固定备择下的相合性.模拟结果显示,在某些备择下,新的检验的功效明显高于原有的基于经验分布函数的检验的功效.     

半参数随机效应模型的异方差检验

在许多实际问题中,检验观察数据是否出现异方差性是一个相当感兴趣的问题.该文研究了半参数随机效应模型的异方差检验问题.基于Lin(1997)的方法,得到了检验方差成分都为零的Score检验统计量.通过随机模拟和实际数值例子,论证了方法的有效性.利用现有的统计软件,容易实现该文所提出的检验方法.     

Beta回归模型的影响诊断

应用曲率方法研究了Beta回归模型的局部影响分析问题,分别在加权扰动、响应变量扰动和自变量扰动模式下得到了相应的影响诊断统计量.同时还讨论了模型中散度参数的齐性检验问题,得到了Score检验统计量.最后通过具体的数值实例说明了所得统计量的有效性.     

离散型半参数广义线性纵向数据模型的方差成分检验

在回归分析中, 随机误差是否存在方差非齐性是大家十分关心的问题, 本文根据Laplace展开原理针对随机效应的影响研究了基于纵向数据的离散型半参数广义线性模型的方差成分检验,得到了Score检验统计量, 最后通过一个实例和计算机模拟验证了本文所提出的方法的有效性.     

非线性结构向量自回归因果图的广义似然比辨识方法

利用图模型方法研究非线性结构向量自回归模型的因果性问题.构建了非线性结构向量自回归因果图模型,提出图模型因果性的广义似然比辨识方法.构造同期因果关系和滞后因果关系的广义似然比统计量,使用bootstrap方法来确定检验统计量的原分布,模拟研究论述了方法的有效性.     

Multiple deletion diagnostics in beta regression models

We consider the problem of identifying multiple outliers in a general class of beta regression models proposed by Ferrari and Cribari-Neto (J Appl Stat 31:799–815, 2004). The currently available single-case deletion diagnostic measures, e.g., the standardized weighted residual (SWR), the Cook-like distance (LD), etc., often fail to identify multiple outlying observations, because they suffer from the well-known problems of masking and swamping effects. In this article, we develop group deletion diagnostic measures, such as generalized SWR, generalized LD, generalized DFFITS and generalized DFBETAS, and suggest a simple procedure for identifying multiple outliers using these. The performance of the proposed methods is investigated through simulation studies and two practical examples.     

线性回归诊断的若干问题

本文对于线性回归诊断提出了几种新的模型和方法。我们首次研究了方差加权和均值漂移的混合模型,得到了相应的诊断统计量。本文还引入了罚函数方法,并以此为工具,讨论了若干有偏估计的影响度量,最后,本文提出了基于重心的诊断统计量,对于识别异常点有较好的效果。     

Spectra of a class of self-affine measures

In the present paper we will study the spectral property of a class of self-affine measures under the condition of compatible pair. We first answer a question of Dutkay and Jorgensen concerning the relationship between spectral self-affine measure and compatible pair. We then consider the spectra of Bernoulli convolutions and obtain a sharp result which extends the corresponding result of Jorgensen, Kornelson and Shuman. Finally, we provide a structural property for the integer spectrum of a spectral self-affine measure.     

Diagnostic Measures for Censored Linear Models based on Empirical Likelihood Method

In this paper, the diagnostic measures for censored linear models are studied based on the empirical likelihood method. First, the diagnostic measures for linear models are studied; Then, the censored linear models are converted to linear models, and the diagnostic measures for converted models are studied; Last, simulation studies and real data analysis are given to illustrate the validity of statistical diagnostic measures.     

Duality relation on spectra of self‐affine measures

The present paper establishes a duality relation for the spectra of self‐affine measures. This is done under the condition of compatible pair and is motivated by a duality conjecture of Dutkay and Jorgensen on the spectrality of self‐affine measures. For the spectral self‐affine measure, we first obtain a structural property of spectra which indicates that one can get new spectra from old ones. We then establish a duality property for the spectra which confirms the conjecture in a certain case.     

具有高斯过程误差的函数型线性模型的统计诊断

提出了具有高斯过程误差的函数型回归模型的几种诊断方法.在此模型中,首先,在样条基的基础上,推导了回归系数函数的估计.随后,证明了数据删失模型和均值漂移模型的等价性.然后,研究了三种诊断方法,即残差分析、Cook距离和似然距离来诊断异常和强影响数据.最后,通过一个模拟例子和一个实例来阐述方法的有效性.     

Balance in complete cohomology

The balance of complete cohomology for modules that admit complete resolutions has been established by Christensen and Jorgensen (2013), as well as by Enochs, Estrada and Iacob (2012), by using two types of constructions on a given bicomplex. In this paper, we show that these constructions are closely related to each other. We also present an alternative proof of balance, which is based on the corresponding assertion for ordinary cohomology.     

Combined regression models

The goal of this paper is two-fold. First, new regression models obtained by combinations of the least squares (LS), minimax (MM), and the least sum of absolute deviations (LSAD) are proposed. Second, measures for assessing the influence of observations on the fitted models are suggested. The paper is interdisciplinary because the theory behind the proposed method draws from results in the operations research area. The methods are illustrated by their application to some examples and graphical illustrations are given.     

自仿测度的非谱准则

设μ_(M,D)是由仿射迭代函数系{φ_d(x)=M~(-1)(x+d)}_(d∈D)唯一确定的自仿测度,它的谱性或非谱性与Hilbert空间L~2(μ_(M,D))中正交指数基(也称为Fourier基)的存在性有着直接的关系.近年来自仿测度μ_(M,D)的谱性或非谱性问题的研究受到人们普遍的关注.本文给出了判定自仿测度μ_(M,D)非谱性的几个充分条件,所得结果改进推广Dutkay,Jorgensen等人的非谱准则.     

非线性回归模型的经验似然诊断

经验似然方法已经被广泛用于线性模型和广义线性模型.本文基于经验似然方法对非线性回归模型进行统计诊断.首先得到模型参数的极大经验似然估计;其次基于经验似然研究了三种不同的影响曲率度量;最后通过一个实际例子,说明了诊断方法的有效性.