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国家自然科学基金(11271355)

作品数:5 被引量:7H指数:2
相关作者:林鹏陈心洁邹国华熊世峰牟唯嫣更多>>
相关机构:中国科学院数学与系统科学研究院北京建筑大学更多>>
发文基金:国家自然科学基金更多>>
相关领域:理学自动化与计算机技术更多>>

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工具变量线性回归模型的平均估计被引量:3
2015年
针对工具变量线性回归模型的未知参数研究了模型平均框架,该框架能同时适用于独立数据和相依数据.在这一框架下,文章推导了模型平均估计的渐近分布,构造了一个覆盖真实参数的概率趋于预定水平的置信区间,并证明了该置信区间与基于全模型的置信区间渐近等价.最后,文章还进行了模型研究,以考察模型平均估计在有限样本下的表现.
陈心洁林鹏
关键词:渐近分布
线性混合效应模型的FIC选择准则被引量:3
2015年
线性混合效应模型在许多科学领域都有重要应用,本文主要研究它的变量选择问题,我们推导了FIC变量选择准则,它通过选择能极小化感兴趣目标量估计的均方误差而提高估计效率。模拟结果表明,本文提出的FIC准则与其他常用的模型选择准则相比具有较大的优势。
陈心洁林鹏邹国华
关键词:混合效应模型
Choice of weights in FMA estimators under general parametric models被引量:1
2013年
The choice of weights in frequentist model average estimators is an important but difficult problem. Liang et al. (2011) suggested a criterion for the choice of weight under a general parametric framework which is termed as the generalized OPT (GOPT) criterion in the present paper. However, no properties and applications of the criterion have been studied. This paper is devoted to the further investigation of the GOPT criterion. We show that how to use this criterion for comparison of some existing weights such as the smoothed AIC-based and BIC-based weights and for the choice between model averaging and model selection. Its connection to the Mallows and ordinary OPT criteria is built. The asymptotic optimality on the criterion in the case of non-random weights is also obtained. Finite sample performance of the GOPT criterion is assessed by simulations. Application to the analysis of two real data sets is presented as well.
ZHANG XinYuZOU GuoHuaLIANG Hua
关于构造多元高斯过程协相关函数的一个注记(英文)
2014年
给出一个简单但较广的构造多响应相依高斯过程协相关函数的方法.该方法仅依赖已有的单响应高斯过程的协相关函数.给出了该方法在计算机实验数据建模中的一些应用.
牟唯嫣熊世峰
关键词:计算机实验
Post-J test inference in non-nested linear regression models
2015年
This paper considers the post-J test inference in non-nested linear regression models. Post-J test inference means that the inference problem is considered by taking the first stage J test into account. We first propose a post-J test estimator and derive its asymptotic distribution. We then consider the test problem of the unknown parameters, and a Wald statistic based on the post-J test estimator is proposed. A simulation study shows that the proposed Wald statistic works perfectly as well as the two-stage test from the view of the empirical size and power in large-sample cases, and when the sample size is small, it is even better. As a result,the new Wald statistic can be used directly to test the hypotheses on the unknown parameters in non-nested linear regression models.
CHEN XinJieFAN YanQinWAN AlanZOU GuoHua
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