Method for multivariate analysis with small sample in aircraft cost estimation

被引：0
|
作者：
Li, Shou'an [1 ,3 ]
Song, Bifeng [1 ,4 ]
Zhang, Hengxi [2 ,4 ]
机构：
[1] Northwestern Polytechnical University, 710072 Xi'an, Shaanxi, China
[2] Air Force Engineering University, 710038 Xi'an, Shaanxi, China
[3] Department of Aircraft Design, Postbox 120, China
[4] Department of Aircraft Design
来源：
| 1600年 / American Institute of Aeronautics and Astronautics Inc.卷 / 44期
关键词：
Partial least-squares regression (PLSR) is applied to multivariate analysis and parametric modeling for estimating aircraft cost-estimating relationship. PLSR method is a statistical tool that has been specially designed to deal with multiple regression where the number of observations is limited; missing data are numerous; and the correlations between variables are high. It is a recent technique that generalizes and combines features from principal component analysis and multiple least-squares regression. Through finding out the outliers in observations; VIP analysis; and the explanatory variable selection; the good relationship for estimating aircraft cost can be derived by PLSR. The application of PLSR to aircraft cost estimation can play a very important role in the cost data analysis;
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摘要：
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