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基于多模型的参数空间预测推断
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作者 陈学前 沈展鹏 +1 位作者 刘信恩 何琴淑 《力学与实践》 北大核心 2015年第4期503-507,共5页
当建立多个模型对工程结构进行数值仿真时,为了得到更可靠的预测结果,需要综合考虑模型选择不确定性和模型形式不确定性对预测结果的影响.联合贝叶斯方法与实验数据计算不同模型的可信度,采用调节因子方法传播模型选择不确定性得到系统... 当建立多个模型对工程结构进行数值仿真时,为了得到更可靠的预测结果,需要综合考虑模型选择不确定性和模型形式不确定性对预测结果的影响.联合贝叶斯方法与实验数据计算不同模型的可信度,采用调节因子方法传播模型选择不确定性得到系统响应置信区间,并叠加模型形式不确定性的影响获得综合模型计算结果的置信区间,再通过插值得到关心量在预测点的置信区间.最后通过某飞行器气动力系数的预测推断检验了该方法的可行性. 展开更多
关键词 模型可信度 贝叶斯理论 调节因子法 模型选择不确定性 模型形式不确定性
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Dynamic Portfolio Choice under Uncertainty about Asset Return Model
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作者 何朝林 孟卫东 《Journal of Donghua University(English Edition)》 EI CAS 2009年第6期645-650,共6页
The effect of uncertainty about stochastic diffusion model on dynamic portfolio choice of an investor who maximizes utility of terminal portfolio wealth was studied.It applied stochastic control method to obtain the c... The effect of uncertainty about stochastic diffusion model on dynamic portfolio choice of an investor who maximizes utility of terminal portfolio wealth was studied.It applied stochastic control method to obtain the closed-form solution of optimal dynamic portfolio,and used the Bayesian rule to estimate the model parameters to do an empirical study on two different samples of Shanghai Exchange Composite Index.Results show,model uncertainty results in positive or negative hedging demand of portfolio,which depends on investor's attitude toward risk;the effect of model uncertainty is more significant with the increasing of investment horizon,the decreasing of investor's risk-aversion degree,and the decreasing of information;predictability of risky asset return increases its allocation in portfolio,at the same time,the effect of model uncertainty also strengthens. 展开更多
关键词 dynamic portfolio model uncertainty estimation risk Bayesian analysis
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FREQUENTIST MODEL AVERAGING ESTIMATION:A REVIEW 被引量:16
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作者 Haiying WANG Xinyu ZHANG Guohua ZOU Academy of Mathematics and Systems Science,Chinese Academy of Sciences,Beijing 100190,China. 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2009年第4期732-748,共17页
In applications, the traditional estimation procedure generally begins with model selection.Once a specific model is selected, subsequent estimation is conducted under the selected model withoutconsideration of the un... In applications, the traditional estimation procedure generally begins with model selection.Once a specific model is selected, subsequent estimation is conducted under the selected model withoutconsideration of the uncertainty from the selection process. This often leads to the underreportingof variability and too optimistic confidence sets. Model averaging estimation is an alternative to thisprocedure, which incorporates model uncertainty into the estimation process. In recent years, therehas been a rising interest in model averaging from the frequentist perspective, and some importantprogresses have been made. In this paper, the theory and methods on frequentist model averagingestimation are surveyed. Some future research topics are also discussed. 展开更多
关键词 Adaptive regression asymptotic theory frequentist model averaging model selection optimality.
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