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带线性误差的部分线性EV模型的经验似然推断 预览
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作者 李晓妍 《统计与决策》 CSSCI 北大核心 2017年第19期18-23,共6页
部分线性EV模型是经典的部分线性模型的推广,在此模型中,假定误差是线性过程。文章把经验似然方法推广到带线性误差的部分线性EV模型,提出了调整的经验对数似然比,并建立了非参数的Wilks定理。
关键词 经验似然 度量误差 线性过程 部分线性模型 卡方分布
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缺失数据下部分线性EV模型的估计及其渐进性质 预览
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作者 夏亚峰 任锋利 《甘肃科学学报》 2015年第6期9-13,共5页
研究了响应变量随机缺失下部分线性测量误差(EV)模型的估计问题。利用核估计和最小二乘的方法给出参数β和非参数g的两步估计,并在适当条件下证明了它们的强相合性和渐近正态性,数值模拟表明第二步估计值比第一步估计值更优。
关键词 部分线性EV模型 缺失数据 强相合性 渐近正态性
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Testing Serial Correlation in Semiparametric Varying-Coefficient Partially Linear EV Models
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作者 Xue-mei Hu Zhi-zhong Wang Feng Liu 《应用数学学报:英文版》 SCIE CSCD 2008年第1期99-116,共18页
<正>This paper studies estimation and serial correlation test of a semiparametric varying-coefficient partially linear EV model of the form Y = Xτβ+ Zτα(T) +ε,ξ= X +ηwith the identifying condition E[(ε,... <正>This paper studies estimation and serial correlation test of a semiparametric varying-coefficient partially linear EV model of the form Y = Xτβ+ Zτα(T) +ε,ξ= X +ηwith the identifying condition E[(ε,ητ)τ] = 0, Cov[(ε,ητ)η] =σ2Ip+1. The estimators of interested regression parametersβ, and the model error varianceσ2, as well as the nonparametric componentsα(T), are constructed. Under some regular conditions, we show that the estimators of the unknown vectorβand the unknown parameterσ2 are strongly consistent and asymptotically normal and that the estimator ofα(T) achieves the optimal strong convergence rate of the usual nonparametric regression. Based on these estimators and asymptotic properties, we propose the VN,p test statistic and empirical log-likelihood ratio statistic for testing serial correlation in the model. The proposed statistics are shown to have asymptotic normal or chi-square distributions under the null hypothesis of no serial correlation. Some simulation studies are conducted to illustrate the finite sample performance of the proposed tests. 展开更多
关键词 变系数模型 偏线性EV模型 最小二乘法 经验似然估计
Estimation in partial linear EV models with replicated observations 被引量:1
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作者 CUI Hengjian 《中国科学:数学英文版》 SCIE 2004年第1期144-159,共16页
The aim of this work is to construct the parameter estimators in the partial linear errors-in-variables (EV) models and explore their asymptotic properties. Unlike other related References, the assumption of known err... The aim of this work is to construct the parameter estimators in the partial linear errors-in-variables (EV) models and explore their asymptotic properties. Unlike other related References, the assumption of known error covariance matrix is removed when the sample can be repeatedly drawn at each designed point from the model. The estimators of interested regression parameters, and the model error variance, as well as the nonparametric function, are constructed. Under some regular conditions, all of the estimators prove strongly consistent. Meanwhile, the asymptotic normality for the estimator of regression parameter is also presented. A simulation study is reported to illustrate our asymptotic results. 展开更多
关键词 PARTIAL linear EV model STRONG consistency replicated observations.
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