在经典的信度理论中,一个保单组合的各风险之间是相互独立的,同时从二次损失函数中推导出信度保费.(Wen et al.,2009)给出了风险间具有共同效应的特殊的相关结构的信度保费表达式.本文在平衡损失函数下考虑此种风险结构的信度理论,特别...在经典的信度理论中,一个保单组合的各风险之间是相互独立的,同时从二次损失函数中推导出信度保费.(Wen et al.,2009)给出了风险间具有共同效应的特殊的相关结构的信度保费表达式.本文在平衡损失函数下考虑此种风险结构的信度理论,特别地得到了Bühlmann和Bühlmann-Straub模型的信度保费表达式.展开更多
The discrete scalar data need prefiltering when transformed by discrete multi-wavelet, but prefiltering will make some properties of multi-wavelets lost. Balanced multi-wavelets can avoid prefiltering. The sufficient ...The discrete scalar data need prefiltering when transformed by discrete multi-wavelet, but prefiltering will make some properties of multi-wavelets lost. Balanced multi-wavelets can avoid prefiltering. The sufficient and necessary condition of p-order balance for multi-wavelets in time domain, the interrelation between balance order and approximation order and the sampling property of balanced multi-wavelets are investigated. The algorithms of 1-order and 2-order balancing for multi-wavelets are obtained. The two algorithms both preserve the orthogonal relation between multi-scaling function and multi-wavelets. More importantly, balancing operation doesnt increase the length of filters, which suggests that a relatively short balanced multi-wavelet can be constructed from an existing unbalanced multi-wavelet as short as possible.展开更多
文摘在经典的信度理论中,一个保单组合的各风险之间是相互独立的,同时从二次损失函数中推导出信度保费.(Wen et al.,2009)给出了风险间具有共同效应的特殊的相关结构的信度保费表达式.本文在平衡损失函数下考虑此种风险结构的信度理论,特别地得到了Bühlmann和Bühlmann-Straub模型的信度保费表达式.
基金Supported by the Scientific Research Foundation for Returned Overseas Chinese Scholars from the State Education Ministry (No. [2002]247) and the Young Key Teachers Foundation of Chongqing University.
文摘The discrete scalar data need prefiltering when transformed by discrete multi-wavelet, but prefiltering will make some properties of multi-wavelets lost. Balanced multi-wavelets can avoid prefiltering. The sufficient and necessary condition of p-order balance for multi-wavelets in time domain, the interrelation between balance order and approximation order and the sampling property of balanced multi-wavelets are investigated. The algorithms of 1-order and 2-order balancing for multi-wavelets are obtained. The two algorithms both preserve the orthogonal relation between multi-scaling function and multi-wavelets. More importantly, balancing operation doesnt increase the length of filters, which suggests that a relatively short balanced multi-wavelet can be constructed from an existing unbalanced multi-wavelet as short as possible.
