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INFERENCE ON THE RANK OF THE GROWTH CURVE MODEL USING MODEL SELECTION METHOD

INFERENCE ON THE RANK OF THE GROWTH CURVE MODEL USING MODEL SELECTION METHOD
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摘要 In this paper we study the estimation of the rank of the parameter trix(RPM) in a growth curve model in the framework of model selection. Following AIC criterion we propose a new general criterion and obtain a strongly consistent estimate of the RPM. We come to our conclusions under the assumptions of normal population and a general case separately. In this paper we study the estimation of the rank of the parameter trix(RPM) in a growth curve model in the framework of model selection. Following AIC criterion we propose a new general criterion and obtain a strongly consistent estimate of the RPM. We come to our conclusions under the assumptions of normal population and a general case separately.
出处 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2001年第2期218-224,共7页 系统科学与复杂性学报(英文版)
基金 This research partially supported by National Natural Science Foundation of China(19631040, 19971085),Ph.D. Program Foundation
关键词 AIC CRITERION EDC CRITERION growth curve MODEL MODEL SELECTION variable selection. AIC criterion, EDC criterion, growth curve model, model selection, variable selection.
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参考文献1

  • 1赵林城.RATES OF A.S.CONVERGENCE OF THE ESTIMATION OF ERROR VARIANCE IN LINEAR MODELS[J].Chinese Annals of Mathematics.1983(01)

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