IMPROVED STRAIGHTFORWARD IMPLEMENTATION OF A STATISTICALLY INSPIRED MODIFICATION OF THE PARTIAL LEAST SQUARES ALGORITHM

ALIN A., Ali M. M.

PAKISTAN JOURNAL OF STATISTICS, vol.28, no.2, pp.217-229, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 28 Issue: 2
  • Publication Date: 2012
  • Journal Name: PAKISTAN JOURNAL OF STATISTICS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.217-229
  • Keywords: Algorithm, Multicollinearity, Multiple Linear Regression, Partial Least Squares, Partial Least Squares regression, SIMPLS, PLS KERNEL ALGORITHM, CROSS-VALIDATION, REGRESSION
  • Dokuz Eylül University Affiliated: Yes

Abstract

Improvement to straightforward implementation of a statistically inspired modification of the partial least squares (SIMPLS) algorithm has been suggested for the case of many explanatory variables, X, and fewer objects, N. The improved SIMPLS algorithm, the SIMPLS algorithm and PLS kernel algorithm have been compared in terms of speed. The results reveal that improvement on the SIMPLS algorithm makes the algorithm much faster than the SIMPLS algorithm. Moreover, the improved algorithm is competitive with or even faster than the PLS kernel algorithm under the considered cases.