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    题名 作者 年代 出处 被引量
1响应变量随机缺失下广义线性模型的经验似然显示文摘研究响应变量随机缺失下广义线性模型的经验似然推断。首先构造未知参数的经验似然比函数,并证明其渐近分布为卡方分布;其次得到参数的若干估计量并得到了其渐近分布,研究结果可以直接构造参数的置信区间或置信域;最后利用模拟计算验证所提方法的优良性质。闫莉 陈夏 2015陕西师范大学学报(自然科学版)2015,43,3:3
2误差为NSD序列的广义线性模型的M估计的强相合性显示文摘研究了以NSD序列(negatively superadditive dependent)为误差的广义线性模型,得到了未知参数的M估计.在较弱的条件下,利用指数不等式、NSD序列加权和的强收敛性和Borel-Cantelli引理等证明了未知参数M估计的强相合性.此结果推广了独立误差和NSD误差的线性模型的相应结果.蔡婷 胡宏昌 2017数学的实践与认识2017,47,19:1
3对数线性Gamma分布模型极大似然估计的强相合性和渐近正态性显示文摘在‖Z‖n=o(log n)和λmin∑i=1nZiZ'i≥cnα(对某个c>0,α>0)等条件下,证明了对数线性Gamma分布模型极大似然估计(MLE)的强相合性和渐近正态性,其中设计阵序列{‖Z‖}n可以为无界序列.刘双花 尹长明 邓娌莉 2015海南师范大学学报(自然科学版)2015,28,2:1
4The Asymptotic Properties of Scad Penalized Generalized Linear Models with Adaptive Designs显示文摘This paper discusses the asymptotic properties of the SCAD(smoothing clipped absolute deviation)penalized quasi-likelihood estimator for generalized linear models with adaptive designs,which extend the related results for independent observations to dependent observations.Under certain conditions,the authors proved that the SCAD penalized method correctly selects covariates with nonzero coefficients with probability converging to one,and the penalized quasi-likelihood estimators of non-zero coefficients have the same asymptotic distribution they would have if the zero coefficients were known in advance.That is,the SCAD estimator has consistency and oracle properties.At last,the results are illustrated by some simulations.GAO Qibing ZHU Chunhua DU Xiuli ZHOU Xingcai YIN Dingxin 2021Journal of Systems Science & Complexity2021,34,2:0
5纵向数据下自适应设计广义估计方程的大样本性质显示文摘广义估计方程(GEE)是分析响应变量是离散或非负的纵向数据回归问题的重要方法.该文在较弱的条件下证明了自适应设计GEE回归参数估计的渐近存在性,相合性和渐近正态性.通过数值模拟验证了估计是有效的.把Xie,Yang(Ann Statist,2003,31:310-347)和Balan,Schiopu-Kratina(Ann Statist,2005,33:522-541)的相应结果推广到了设计阵是自适应情形,并且对Fisher信息阵特征根的要求降到最低.尹长明 石岳鑫 2021数学物理学报(A辑)2021,41,6:0
6Law of iterated logarithm and model selection consistency for generalized linear models with independent and dependent responses显示文摘We study the law of the iterated logarithm (LIL) for the maximum likelihood estimation of the parameters (as a convex optimization problem) in the generalized linear models with independent or weakly dependent (ρ-mixing) responses under mild conditions. The LIL is useful to derive the asymptotic bounds for the discrepancy between the empirical process of the log-likelihood function and the true log-likelihood. The strong consistency of some penalized likelihood-based model selection criteria can be shown as an application of the LIL. Under some regularity conditions, the model selection criterion will be helpful to select the simplest correct model almost surely when the penalty term increases with the model dimension, and the penalty term has an order higher than O(log log n) but lower than O(n). Simulation studies are implemented to verify the selection consistency of Bayesian information criterion.Xiaowei YANG Shuang SONG Huiming ZHANG 2021Frontiers of Mathematics in China2021,16,3:0
7惩罚项GLM算法下的数据分析岗位薪资影响因素分析显示文摘为了从样本量庞大、岗位描述多样复杂的招聘数据中获取与薪资显著相关的变量,探究数据分析岗位薪资的影响因素。本文将惩罚因子法和广义线性回归模型结合进行变量选择,提出了LASSO-GLM算法、SCAD-GLM算法和Adaptive LASSO-GLM算法。以均方误差作为三种算法的评价准则,选取出最适合本案例的Adaptive LASSO-GLM算法进行薪资影响因素分析。结果表明,应聘者的工作经验年限、学历高低、掌握的软件、公司类型和公司所在地会对数据分析岗位的薪资造成显著影响,从而为数据分析相关岗位的应聘人员提供就业方向及就业学习指导。余婉露 张斯杰 2023产业与科技论坛2023,22,17:0
8误差不相关广义线性模型极大拟似然估计的收敛速度显示文摘在广义线性模型(GLM)中,设yi和Zi分别是响应变量和回归系数向量.若随机误差ei=yi-Eyi,i=1,2,…不相关,且sup var(ei)<∞,sup‖Zi‖2<∞,λn→∞和一些光滑条件满足,i≥1i≥1该文证明了一般联系函数GLM回归参数极大拟似然估计βn是弱相合的,具有收敛速度‖β-β0‖=Op(λn-1/2)n),其中λn是i∑i=1ZiZ′的最小特征根,β0是回归参数向量真值.尹长明 刘双花 陈波红 2015华中师范大学学报(自然科学版)2015,49,5:0
9Empirical Likelihood in Generalized Linear Models with Working Covariance Matrix显示文摘Empirical likelihood in generalized linear models with multivariate responses and working covariance matrix is discussed.Under the weakest assumption on eigenvalues of Fisher’s information matrix and some other regular conditions,we prove that the non-parametric Wilk’s property still holds,that is,the empirical log-likelihood ratio at the true parameter values converges to the standard chi-square distribution.Numerical simulations are given to verify our theoretical result.Xiu-qing ZHOU Qi-bing GAO Chun-hua ZHU Xiu-li DU Liu-liu MAO 2022Acta Mathematicae Applicatae Sinica2022,38,1:0
10固定和自适应设计下高维广义线性模型的经验似然检验显示文摘利用经验似然方法,讨论固定设计和自适应设计下高维广义线性模型中的参数检验问题。数值计算结果表明,所构造的经验对数似然比统计量渐近于标准卡方分布,具有较稳定的真实检验水平和功效。白璐 陈夏 2018陕西师范大学学报(自然科学版)2018,46,4:0
11自适应设计广义线性模型的自适应Lasso惩罚最小二乘的渐近性质显示文摘针对自适应设计广义线性模型,研究自适应Lasso惩罚最小二乘变量选择方法。在一定条件下,得到自适应Lasso惩罚最小二乘估计的相合性和Oracle性质,该结果将固定设计广义线性模型相关结果推广到自适应设计广义线性模型中。通过模拟可知,自适应Lasso惩罚方法优于Lasso惩罚方法。高启兵 于欢 时倩倩 朱桂梅 2022陕西师范大学学报(自然科学版)2022,50,3:0
12Asymptotic Properties of Maximum Quasi-Likelihood Estimators in Generalized Linear Models with Diverging Number of Covariates显示文摘GAO Qibing DU Xiuli ZHOU Xiuqing XIE Fengchang 2018Journal of Systems Science & Complexity2018,31,5:0
13独立与相依情形下加权广义线性模型选择的重对数律和强一致性显示文摘在温和条件下,考虑相依响应情形(ρ-混合或m-相依),针对一般广义线性模型(GLM)任意改变其参数权重构造出加权GLM,给出了参数的最大似然估计(MLE),并推导了加权后模型的重对数律(LIL)。应用独立情形下强极限理论证明了任意修正模型与全模型的对数似然之差的渐近结果。借助惩罚加权对数似然函数技术,基于相依LIL证明了模型选择准则的强一致性,并推导出若惩罚项的阶数介于O(log log n)与O(n)之间时,则该准则选取最简单修正模型几乎是必然的。杨晓伟 赵开斌 刘相国 王冬银 2020宜春学院学报2020,42,3:0
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