具有线性趋势回归信度模型异方差的score检验

回归信度模型在保险研究中具有重要的作用.本文分险种内部,险种之间,险种内部及之间三种情形讨论了具有线性趋势回归信度模型异方差的score检验问题.首先推导了异方差存在性检验的score检验统计量,然后利用Monte-Carlo方法模拟了这几种检验统计量的功效,功效模拟结果显示：这几种检验统计量都有很好的检验效果.最后利用文中所得到的检验方法对旅客意外身体伤害保险数据进行了实例分析.     

具有ARIMA(0,1,0)误差的非线性模型的异方差检验

本文讨论随机误差是 ARIMA( 0 ,1 ,0 )序列的非线性回归模型的异方差检验问题 .首先导出了检验的 score统计量 ,然后利用参数的正交变换 ,得到了调整的 score统计量 .最后 ,利用氯化物数据 ( Bates &Watts,1 988)说明了检验方法的应用     

具有线性趋势回归信度模型的自相关性的score检验

回归信度模型在保险研究中具有重要的作用。本文讨论了具有线性趋势回归信度模型自相关性的score检验问题。首先推导出模型中自相关存在性检验的score检验统计量,然后利用Monte-Carlo方法模拟了此种检验统计量的功效。最后利用文中所得到的检验方法对旅客意外身体伤害保险数据进行了实例分析。     

具有椭球误差的线性一致相关模型的相关性检验

本文讨论具有椭球误差的线性一致相关模型的相关性检验问题.基于Fisher-score方法给出模型参数估计的迭代公式,然后分别对一致相关系数进行了存在性和齐性检验,得到了相应检验的score统计量,同时给出了功效模拟.最后利用实际数据说明了模型以及检验统计量的价值.     

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.     

基于重复测量数据的Poisson回归模型的偏大离差的Score检验

Poisson回归模型广泛应用于分析计数型数据 ,Dean&Lawless(1989)和Dean(1992 )讨论了非重复测量得到的计数型数据的偏大离差存在性的检验问题 .本文分别利用随机系数模型和对数非线性模型讨论了基于重复测量得到的计数型数据的偏大离差的检验问题 ,得到了检验的score统计量 .     

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.     

非线性纵向数据模型中自相关性和随机效应的存在性检验

刻画纵向数据协方差结构有三种可能因素 ,即序列相关 (特别是一阶自相关 )、随机效应和常规的随机误差 (Diggleetal,2 0 0 2 ) .本文研究非线性纵向数据模型的自相关性和随机效应存在性的单个和联合检验 ,得到了检验的score统计量 ,并利用血浆药物渗透数据 (Davidian&Gilinan ,1 995)说明检验方法的应用 .     

具有一致相关的纵向数据模型中方差和相关系数的齐性检验

在纵向数据分析中, 模型方差的齐性是一个基本假定, 但是该假定未必正确. 林金官、韦博成^[1]讨论了具有AR(1)误差的非线性纵向数据模型中方差和相关系数的齐性检验. 本文对具有一致相关协方差结构的纵向数据模型, 研究了方差齐性和相关系数齐性的检验, 得到了检验的score统计量, 并应用于葡萄糖数据. 最后, 本文还给出了模拟结果.     

具有ARIMA（0，1，0）对称误差的非线性模型的统计诊断

本文讨论具有ARIMA(0,1,0)对称误差的非线性模型的异方差检验和局部影响分析.对称误差分布族包括正态,t,power exponential,logistics Ⅰ,Ⅱ,污染正态等所有对称连续分布.文章首先导出了关于白噪声异方差检验的score统计量及其调整形式,然后对模型进行了局部影响分析,得到了基于似然函数扰动和反应变量扰动的诊断统计量.最后,利用实际数据说明了检验方法的应用,并用Monte Carlo模拟方法研究了异方差检验统计量的检验功效.     

A Partial Empirical Likelihood Based Score Test Under a Semiparametric Finite Mixture Model

We propose a score statistic to test the null hypothesis that the two-component density functions are equal under a semiparametric finite mixture model. The proposed score test is based on a partial empirical likelihood function under an I-sample semiparametric model. The proposed score statistic has an asymptotic chi-squared distribution under the null hypothesis and an asymptotic noncentral chi-squared distribution under local alternatives to the null hypothesis. Moreover, we show that the proposed score test is asymptotically equivalent to a partial empirical likelihood ratio test and a Wald test. We present some results on a simulation study.     

APPROXIMATE POWER OF HETEROSCEDASTICITY TEST IN NONLINEAR MODELS WITH ARIMA（0,1,0） ERRORS

This paper presents an approach for estimating power of the score test, based on an asymptotic approximation to the power of the score test under contiguous alternatives. The method is applied to the problem of power calculations for the score test of heteroscedasticity in European rabbit data （Ratkowsky, 1983）. Simulation studies are presented which indicate that the asymptotic approximation to the finite-sample situation is good over a wide range of parameter configurations.     

离散型指数族非线性模型的变离差检验

It is necessary to test for varying dispersion in generalized nonlinear models. Wei,et al (1998) developed a likelihood ratio test,a score test and their adjustments to test for varying dispersion in continuous exponential family nonlinear models. This type of problem in the framework of general discrete exponential family nonlinear models is discussed. Two types of varying dispersion, which are random coefficients model and random effects model, are proposed ,and corresponding score test statistics are constructed and expressed in simple ,easy to use ,matrix formulas.     

TESTING FOR VARYING DISPERSION IN DISCRETE EXPONENTIAL FAMILY NONLINEAR MODELS

§ 1　 Introduction and modelsThe general form of exponential family nonlinear models isg(μi) =f(xi,﹀) , (1 )where,g(· ) is a monotonic link function,f is a known differentiable nonlinear functionand﹀ is a p-vectoroffixed population parameters;μi=E(yi) and the density of response yiisp(yi) =exp{[yiθi -b(θi) -c(yi) ] -12 a(yi,) } ,(2 )whereθi is the natural parameter, is the dispersion parameter.From [1 1 ] ,μi=b(θi) ,Vi=Var(yi) =- 1 b(θi) .If f(xi,β) =x Ti ﹀,then mod…     

平衡单向分类随机效应模型中的多个异常值检验

该文研究平衡单向分类随机效应模型中多个异常值的检验问题. 在基于随机效应上的均值滑动模型下导出了似然比检验统计量, 并给出了其精确分布及水平异常值的检验过程. 在基于观测误差上的均值滑动模型下,利用得分检验统计量给出了多个异常值的检验过程.     

带有约束条件的方差扩大模型的Score检验

本对带有的约束条件的约性模型方差扩大模型的假检测问题给出了Score检验统计量,指出两个主要的结果。     

Some Properties of A Lack-of-Fit Test for a Linear Errors in Variables Model

The relationship between the linear errors-in-variables model and the corresponding ordinary linear model in statistical inference is studied. It is shown that normality of the distribution of covariate is a necessary and sufficient condition for the equivalence. Therefore, testing for lack-of-fit in linear errors-in-variables model can be converted into testing for it in the corresponding ordinary linear model under normality assumption. A test of score type is constructed and the limiting chi-squared distribution is derived under the null hypothesis.Furthermore, we discuss the power of the test and the choice of the weight function involved in the test statistic.     

A Score Type Test for General Autoregressive Models in Time Series

This paper is devoted to the goodness-of-fit test for the general autoregressive models in time series. By averaging for the weighted residuals, we construct a score type test which is asymptotically standard chi-squared under the null and has some desirable power properties under the alternatives. Specifically, the test is sensitive to alternatives and can detect the alternatives approaching, along a direction, the null at a rate that is arbitrarily close to n-1/2. Furthermore, when the alternatives are not directional, we construct asymptotically distribution-free maximin tests for a large class of alternatives. The performance of the tests is evaluated through simulation studies.