抽象的

Unary linear regression method on principal component analysis

Xu Li-Li


Only dependent variable is considered as random variables in commonly-used linear regression methods, so the regression results will be changed according with the coordinates selection. Enlightened by the method of principal component analysis (PCA), a new unary linear regression which is irrelevant to coordinates is proposed, which is the PCA based method. Compared with conventional least squares method, the new method possesses the advantages of lower deviation error and higher regression accuracy, which is verified by simulation cases and living examples. The simulation case and living example verified new method less system deviation and better regression accuracy than conventional. PCA is numerical solution, the advantage of low calculation amount makes it own a broad application prospect.


索引于

  • 中国社会科学院
  • 谷歌学术
  • 打开 J 门
  • 中国知网(CNKI)
  • 引用因子
  • 宇宙IF
  • 研究期刊索引目录 (DRJI)
  • 秘密搜索引擎实验室
  • 欧洲酒吧
  • ICMJE

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