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混合相依过程局部多项式加权回归估计渐近正态性的进一步结果 被引量:1
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作者 王成军 褚标 《四川大学学报(自然科学版)》 CAS CSCD 北大核心 2002年第4期608-616,共9页
对相依时间序列数据 ,在一定的条件下已有人证明了局部多项式加权回归系数估计服从渐近正态分布 ,其中核函数是有界的 .但在非线性相依过程 (如 ρ 混合过程和强混合过程 )中 ,当数据之间的相依程度较大时 ,这种核函数便失去其合理性 ,... 对相依时间序列数据 ,在一定的条件下已有人证明了局部多项式加权回归系数估计服从渐近正态分布 ,其中核函数是有界的 .但在非线性相依过程 (如 ρ 混合过程和强混合过程 )中 ,当数据之间的相依程度较大时 ,这种核函数便失去其合理性 ,作者在更广泛的核函数空间上考虑了这个问题 。 展开更多
关键词 混合相依过程 加权回归估计 渐近正态性 ρ-混合过程 强混合过程 核函数 广义局部多项式 相依时间序列 非参数估计
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强混合序列下非参回归函数加权核估计的强收敛速度 被引量:1
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作者 罗中德 《广西科学》 CAS 2013年第1期17-21,共5页
在误差项为强混合序列的条件下,利用随机变量部分和的矩不等式,讨论非参回归函数加权核估计的强相合性,给出其收敛速度.当样本矩足够大时,强相合的收敛速度约等于n-1/2.
关键词 强混合过程 非参回归函数 加权核估计 收敛速度
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Novel Optimization Approach to Mixing Process Intensification
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作者 郭凯 刘伯潭 +1 位作者 李奇 刘春江 《Transactions of Tianjin University》 EI CAS 2015年第1期1-10,共10页
An approach was presented to intensify the mixing process. Firstly, a novel concept, the dissipation of mass transfer ability(DMA) associated with convective mass transfer, was defined via an analogy to the heat-work ... An approach was presented to intensify the mixing process. Firstly, a novel concept, the dissipation of mass transfer ability(DMA) associated with convective mass transfer, was defined via an analogy to the heat-work conversion. Accordingly, the focus on mass transfer enhancement can be shifted to seek the extremum of the DMA of the system. To this end, an optimization principle was proposed. A mathematical model was then developed to formulate the optimization into a variational problem. Subsequently, the intensification of the mixing process for a gas mixture in a micro-tube was provided to demonstrate the proposed principle. In the demonstration example, an optimized velocity field was obtained in which the mixing ability was improved, i.e., the mixing process should be intensified by adjusting the velocity field in related equipment. Therefore, a specific procedure was provided to produce a mixer with geometric irregularities associated with an ideal velocity. 展开更多
关键词 convective mass transfer mass transfer ability flow pattern optimization calculus of variations porous media model
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