跳到主要导航 跳到搜索 跳到主要内容

Fast algorithm of Gram-Schmidt regression method

  • Huiwen Wang*
  • , Bang Xia
  • , Jie Meng
  • *此作品的通讯作者
  • Beihang University
  • Central University of Finance and Economics

科研成果: 期刊稿件 › 文章 › 同行评审

摘要

A new multiple linear regression method was proposed which can screen the variables fast. In the modeling process, not only can it screen variables containing best information to explain the dependent variable, but also distinguish and test redundant variables in the model based on Gram-Schmidt orthogonal transformation, so as to timely strike out all the redundant information in quantity. The simulation analysis shows that compared to classic stepwise regression this new method has a higher arithmetic speed and the modeling process is briefer and more efficient, when the variables appear in a large quantity and have a pretty serious server multicollinearity at the same time.

源语言英语
页(从-至)1259-1262+1268
期刊Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics
卷39
期9
出版状态已出版 - 9月 2013

学术指纹

探究 'Fast algorithm of Gram-Schmidt regression method' 的科研主题。它们共同构成独一无二的学术指纹。

引用此