| COMMENTS ON THE NIPALS ALGORITHM |
| |
| 作者姓名： | YOSHIKATSU MIYASHITA TOSHIAKI ITOZAWA HIROYUKI KATSUMI SHIN-ICHI SASAKI |
| |
| 作者单位： | YOSHIKATSU MIYASHITA TOSHIAKI ITOZAWA HIROYUKI KATSUMI SHIN-ICHI SASAKI Department of Knowledge-Based Information Engineering，Toyohashi University of Technology，Tempaku.Toyohashi 440，Japan |
| |
| 摘 要： | The Non-linear lterative Partial Least Squares(NIPALS)algorithm is used in principal componentanalysis to decompose a data matrix into score vectors and eigenvectors(loading vectors)plus a residualmatrix.N1PALS starts with some guessed starting vector.The principal components obtained by NIPALSdepends on the starting vector;the first principal component could not always be computed.Wold hassuggested a starting vector for NIPALS,but we have found that even if this starting vector is used,thefirst principal component cannot be obtained in all cases.The reason why such a situation occurs isexplained by the power method.A simple modification of the original NIPALS procedure to avoid gettingsmaller eigenvalues is presented.
|
COMMENTS ON THE NIPALS ALGORITHM |
| |
| YOSHIKATSU MIYASHITA TOSHIAKI ITOZAWA HIROYUKI KATSUMI SHIN-ICHI SASAKI.COMMENTS ON THE NIPALS ALGORITHM[J].Journal of Geographical Sciences,1990(1). |
| |
| Authors: | YOSHIKATSU MIYASHITA TOSHIAKI ITOZAWA HIROYUKI KATSUMI SHIN-ICHI SASAKI |
| |
| Institution: | YOSHIKATSU MIYASHITA TOSHIAKI ITOZAWA HIROYUKI KATSUMI SHIN-ICHI SASAKI Department of Knowledge-Based Information Engineering,Toyohashi University of Technology,Tempaku.Toyohashi,Japan |
| |
| Abstract: | The Non-linear lterative Partial Least Squares(NIPALS)algorithm is used in principal component analysis to decompose a data matrix into score vectors and eigenvectors(loading vectors)plus a residual matrix.N1PALS starts with some guessed starting vector.The principal components obtained by NIPALS depends on the starting vector;the first principal component could not always be computed.Wold has suggested a starting vector for NIPALS,but we have found that even if this starting vector is used,the first principal component cannot be obtained in all cases.The reason why such a situation occurs is explained by the power method.A simple modification of the original NIPALS procedure to avoid getting smaller eigenvalues is presented. |
| |
| Keywords: | Matrix decomposition NIPALS Principal component SIMCA PLS |
| 本文献已被 CNKI 等数据库收录！ |
| 点击此处可从《地理学报(英文版)》浏览原始摘要信息 |
| 点击此处可从《地理学报(英文版)》下载免费的PDF全文 |
