讨论矩约束条件下的广义经验似然比统计量族以及相应的性质。此统计量实际上是B aggerly(1998)所介绍的广义经验似然比统计量的一种推广。在一定条件下,证明了此分布族中的统计量与Ow en(1988)和Q in and L aw less(1994)的经验似然是...讨论矩约束条件下的广义经验似然比统计量族以及相应的性质。此统计量实际上是B aggerly(1998)所介绍的广义经验似然比统计量的一种推广。在一定条件下,证明了此分布族中的统计量与Ow en(1988)和Q in and L aw less(1994)的经验似然是一阶渐近等价的。因此,这些统计量的分布均是渐近于2χ分布,相应的估计也都满足相合性和渐近正态性。展开更多
Generalized linear measurement error models, such as Gaussian regression, Poisson regression and logistic regression, are considered. To eliminate the effects of measurement error on parameter estimation, a corrected ...Generalized linear measurement error models, such as Gaussian regression, Poisson regression and logistic regression, are considered. To eliminate the effects of measurement error on parameter estimation, a corrected empirical likelihood method is proposed to make statistical inference for a class of generalized linear measurement error models based on the moment identities of the corrected score function. The asymptotic distribution of the empirical log-likelihood ratio for the regression parameter is proved to be a Chi-squared distribution under some regularity conditions. The corresponding maximum empirical likelihood estimator of the regression parameter π is derived, and the asymptotic normality is shown. Furthermore, we consider the construction of the confidence intervals for one component of the regression parameter by using the partial profile empirical likelihood. Simulation studies are conducted to assess the finite sample performance. A real data set from the ACTG 175 study is used for illustrating the proposed method.展开更多
文摘讨论矩约束条件下的广义经验似然比统计量族以及相应的性质。此统计量实际上是B aggerly(1998)所介绍的广义经验似然比统计量的一种推广。在一定条件下,证明了此分布族中的统计量与Ow en(1988)和Q in and L aw less(1994)的经验似然是一阶渐近等价的。因此,这些统计量的分布均是渐近于2χ分布,相应的估计也都满足相合性和渐近正态性。
基金supported by National Natural Science Foundation of China(Grant Nos.11301569,11471029 and 11101014)the Beijing Natural Science Foundation(Grant No.1142002)+2 种基金the Science and Technology Project of Beijing Municipal Education Commission(Grant No.KM201410005010)Hong Kong Research Grant(Grant No.HKBU202711)Hong Kong Baptist University FRG Grants(Grant Nos.FRG2/11-12/110 and FRG1/13-14/018)
文摘Generalized linear measurement error models, such as Gaussian regression, Poisson regression and logistic regression, are considered. To eliminate the effects of measurement error on parameter estimation, a corrected empirical likelihood method is proposed to make statistical inference for a class of generalized linear measurement error models based on the moment identities of the corrected score function. The asymptotic distribution of the empirical log-likelihood ratio for the regression parameter is proved to be a Chi-squared distribution under some regularity conditions. The corresponding maximum empirical likelihood estimator of the regression parameter π is derived, and the asymptotic normality is shown. Furthermore, we consider the construction of the confidence intervals for one component of the regression parameter by using the partial profile empirical likelihood. Simulation studies are conducted to assess the finite sample performance. A real data set from the ACTG 175 study is used for illustrating the proposed method.