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The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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0下载:
The proposed approach is based on three stages which (1) use neural networks for constructing a response
function model of a dynamic multiresponse system, (2) use exponential desirability functions for evaluating
overall performance of a specific
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6下载:
动态分层因子模型的估计程序,在matlab里面即可运行,里面readme有详细介绍-Dynamic hierarchical factor model
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动态因子模型,该模型可以有效对高维数据进行降维,将成百上千的数据信息浓缩在几个因子里面,即从一国许多经济时间序列数据中估计和解释驱动各变量波动的共同动态因子。 MATLAB代码(dynamic factor model, the model can be effective for high-dimensional data dimension reduction, condensed the hundreds of thousands of data in several factors,
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动态因子分层模型,用于经济分析商品初期价格,内容四层动态因子分析模型(Dynamic factor hierarchical model, which is used to analyze the initial price of goods economically, and four level dynamic factor analysis model of content)
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卡马乔的混频马尔科夫区制转换动态因子模型程序(Markov swtiching dynamic factor model program with GAUSS)
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