A New Approach to Robust Partial Least Squares Regression Analysis

Journal Title: INTERNATIONAL JOURNAL OF MATHEMATICS TRENDS AND TECHNOLOGY - Year 2014, Vol 9, Issue 3

Abstract

Partial Least Squares Regression (PLSR) is a linear regression technique developed to relate many independent variables to one or several dependent variables. Robust methods are introduced to reduce or remove the effects of outlying data points. In the previous studies in robust PLSR field it has been mentioned that if the sample covariance matrix is properly robustified further robustification of the linear regression steps of the PLS1 algorithm (PLSR with univariate dependent variable) becomes unnecessary. Therefore, the purpose of this study is to propose a new approach to robust PLSR based on statistical procedures for covariance matrix robustification by selecting the well-known S-estimators. Both simulation results and an analysis on a real data set, which is used in robust PLSR literature frequently, showing the effectiveness, success in fitting to regular data points and predictive power of the new proposed robust PLSR method.

Authors and Affiliations

Esra Polat , Suleyman Gunay

Keywords

Related Articles

Multi-Agent Coalition Formation for Course Selection Strategies in E-Learning System

Multi Agent Systems are being used in a wide variety of applications, ranging from comparatively small systems for personal assistance, to open, complex, systems for industrial applications. In e-learning, Multi Agent Sy...

On Most Generalized Topologies on a Non Empty Set

The purpose of this paper is to introduce a notion of continuity called (G ,D)- continuity between two non empty sets X and Y, and its relationships with other functions are studied.

Fixed points for α-ᴪ Contractive Mapping in 2-Metric spaces

In this paper, we introduce the notion of α-ᴪ contractive type mappings in 2-metric spaces and establish fixed point theorems for these mappings.

Fuzzy Transportation Problem Using Improved Fuzzy Russells Method

In this paper, we investigate the new idea of optimal solution of squared triangular and trapezoidal fuzzy number via fuzzy russal’s method. This method is a modification of yager’s ranking method. A new algorithm is inv...

Some Fixed Point Results in Dislocated Quasi-Metric Space

In this paper, we prove some fixed point theorems for different contraction mappings in dislocated quasi-metric space. The results presented in this paper extend and improve several well-known results in the literature....

Download PDF file
  • EP ID EP152632
  • DOI -
  • Views 254
  • Downloads 0

How To Cite

Esra Polat, Suleyman Gunay (2014). A New Approach to Robust Partial Least Squares Regression Analysis. INTERNATIONAL JOURNAL OF MATHEMATICS TRENDS AND TECHNOLOGY, 9(3), 197-205. https://europub.co.uk/articles/-A-152632