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对指数族非线性混合效应模型, 本文基于$Q$函数(朱宏图, 2001)方法, 给出几种度量数据删除影响的统计量\bd 其主要思想是将随机效应视为缺失数据, 并利用EM算法来处理完全数据对数似然函数的条件期望\bd 一个实际例子说明我们方法是有效的 相似文献
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《应用概率统计》2019,(3)
在有限总体推断问题中,辅助总体信息是经常可获取的.经验似然方法己被证实是一种非常灵活和有用的工具来处理这类问题.在两样本密度比模型下,本文考虑了基准分布的总体均值的经验似然推断问题.对基于密度比模型的经验似然而言,对偶似然是一种便利的技术工具,尽管它与标准的经验似然具有相同的极值点和极值,但是它却不能方便地把此类辅助信息引入到似然函数里,因此会导致效率损失.相对而言,Qin和Lawless~([21])提出的标准的经验似然方法不会有此问题,且能方便地引入辅助信息.基于使用辅助信息的经验似然和对偶似然方法,我们构建了点估计和区间估计,并做了仔细的比较.模拟发现,尽管使用辅助信息的经验似然方法得到的点估计的效率提升很小,但是区间估计在一些情形下却有明显的差别.拿覆盖精度来说,在无偏或适当有偏的总体分布下,两种方法得到的区间估计是可比的,但当总体严重有偏时,前者的区间估计明显优于后者. 相似文献
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本文使用蒙特卡罗方法, 求得广义线性混合模型之最大似然估计, 并提供用来评估统计参数之收敛和精确度之实用方法\bd 仿真研究显示无偏之固定效应参数估计, 而方差分量估计之误差则相近于前人结果\bd 应用举例为使用泊松分布求取乳癌死亡率之小区域估计. 相似文献
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在医学研究中,常常使用受试者操作特性曲线(ROC)曲线来研究两样本的比较问题。Lloyd构造了ROC曲线的核平滑估计,并给出了其渐近偏差以及渐近标准差。此外,当还可以获悉某一处理组上的辅助信息时,Zhou,Zhou & Ma利用经验似然的方法构造了ROC曲线的核平滑经验似然估计。本文利用"亏量"这个概念比较了带有辅助信息的情况下,对核平滑经验似然估计与完全经验似然估计进行了比较。并给出了核平滑经验似然估计优于完全经验似然估计的结论,并且随着样本容量的增大,该亏量也是无限增大的。 相似文献
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Empirical Likelihood Inference Under Stratified Random Sampling in the Presence of Measurement Error 总被引:1,自引:0,他引:1
Chang-chun Wu Run-chu Zhang 《应用数学学报(英文版)》2005,21(3):429-440
Suppose that several different imperfect instruments and one perfect instrument are used independently to measure some characteristic of a population. In order to make full use of the sample information, in this paper the empirical likelihood method is put forward for making inferences on parameters of interest under stratified random sampling in the presence of measurement error, Our results show that it can lead to estimators which are asymptotically normal and utilize all the available sample information. We also obtain the asymptotic distribution of empirical likelihood testing statistics. In particular, we apply the method to obtain estimator and confidence interval of population mean. 相似文献
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Auxiliary population information is often available in finite population inference problems, and the empirical likelihood (EL) approach has been demonstrated to be flexible and useful for such problems. The present paper concerns EL when interest centers on inference for the mean of the baseline distribution under two-sample density ratio models. Although dual EL is a convenient technical tool since it has the same maximum point and maximum likelihood as DRM-based EL, it can not combine such auxiliary information into the likelihood conveniently and may have loss of efficiency. By contrast, the classical EL approach of Qin and
Lawless\ucite{21} does not have this problem and incorporate seamlessly auxiliary information. Based on the EL using auxiliary information and the
dual EL methods, we construct both point and interval estimations and make a careful comparison. Though the point estimation efficiency gain obtained
by the former is not noticeable, we find that they may have different performances in interval estimation. In terms of coverage accuracy, the two intervals are comparable for not or moderate skewed populations, and the EL interval using auxiliary information can be much superior for severely skewed populations. 相似文献
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���: ���� 《应用概率统计》2006,35(3):305-316
??Auxiliary population information is often available in finite population inference problems, and the empirical likelihood (EL) approach has been demonstrated to be flexible and useful for such problems. The present paper concerns EL when interest centers on inference for the mean of the baseline distribution under two-sample density ratio models. Although dual EL is a convenient technical tool since it has the same maximum point and maximum likelihood as DRM-based EL, it can not combine such auxiliary information into the likelihood conveniently and may have loss of efficiency. By contrast, the classical EL approach of Qin and
Lawless\ucite{21} does not have this problem and incorporate seamlessly auxiliary information. Based on the EL using auxiliary information and the
dual EL methods, we construct both point and interval estimations and make a careful comparison. Though the point estimation efficiency gain obtained
by the former is not noticeable, we find that they may have different performances in interval estimation. In terms of coverage accuracy, the two intervals are comparable for not or moderate skewed populations, and the EL interval using auxiliary information can be much superior for severely skewed populations. 相似文献
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Pseudo-empirical likelihood estimation of the population mean is considered. A nonparametric regression theory is proposed, to provide the fitted values on which to calibrate, and the common model misspecification problem is therefore addressed. Results derived from empirical studies show that the proposed estimator for the population mean can perform better than alternative estimators. 相似文献
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CHEN Li & SHI Jian School of Mathematics Statistics Yunnan University Kunming China Academy of Mathematics Systems Science Chinese Academy of Sciences Beijing 《中国科学 数学(英文版)》2011,(9)
Hypothesis test on the population mean with various inequality constraints is studied in this paper.The empirical likelihood method is applied to construct test statistics.Limiting distributions of the empirical likelihood ratio test statistics are proven to be a weighted mixture of chi-square distributions.Numerical results are presented to show the validity of the proposed method. 相似文献
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考虑了在有辅助信息情况下对M-泛函的一约束集进行统计检验的问题.我们定义了经验似然比检验统计量,并获得了它们的渐近分布. 相似文献
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EMPIRICAL LIKELIHOOD RATIO CONFIDENCE INTERVALS FOR VARIOUS DIFFERENCES OF TWO POPULATIONS 总被引:1,自引:0,他引:1
Recently the empirical likelihood has been shown to be very useful in nonparametric models. Qin combined the empirical likelihood thought and the parametric likelihood method to construct confidence intervals for the difference of two population means in a semiparametric model. In this paper, we use the empirical likelihood thought to construct confidence intervals for some differences of two populations in a nonparametric model. A version of Wilks' theorem is developed. 相似文献
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本文利用了强平稳$m-$相依序列的特殊性质,讨论了$m-$相依序列密度函数的经验似然推断, 给出了似然比统计量的极限分布,可构造参数的经验似然置信区间. 并且通过模拟计算来说明有限样本下应用经验似然方法的合理性. 相似文献
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In this paper, we propose an information-theoretic approach to the effective usage of auxiliary information from survey data,
which is suitable for both simple and complex survey data. Our estimator under simple random sampling without replacement
will be consistent and asymptotically normal. We show that the resulting estimates have smaller asymptotic variances than
the usual estimates which do not use auxiliary information. For more complex survey designs, the resulting estimator is in
essence asymptotically equivalent to a pseudo empirical likelihood estimator. Results of a limited simulation study show that
the proposed estimators perform well among a number of competitors. 相似文献