On Some Aspects of Variable Selection for Partial Least Squares Regression Models

2008 ◽  
Vol 27 (3) ◽  
pp. 302-313 ◽  
Author(s):  
Partha Pratim Roy ◽  
Kunal Roy
Keyword(s):  
Variable Selection ◽  
Least Squares ◽  
Partial Least Squares ◽  
Regression Models ◽  
Partial Least Squares Regression ◽  
Least Squares Regression ◽  
Selection For

Prediction of Long-Residue Properties of Potential Blends from Mathematically Mixed Infrared Spectra of Pure Crude Oils by Partial Least-Squares Regression Models

2009 ◽  
Vol 23 (4) ◽  
pp. 2164-2168 ◽  
Author(s):  
Peter de Peinder ◽  
Tom Visser ◽  
Derek D. Petrauskas ◽  
Fabien Salvatori ◽  
Fouad Soulimani ◽  
...  
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Infrared Spectra ◽  
Regression Models ◽  
Partial Least Squares Regression ◽  
Crude Oils ◽  
Least Squares Regression

Optimization Study of Stepwise Regression and Partial Least Squares Regression Models for Dam Security Monitoring

2014 ◽  
Vol 578-579 ◽  
pp. 1101-1107 ◽  
Author(s):  
Wei Ling Hu ◽  
Nian Wu Deng ◽  
Qiu Shi Liu
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Regression Models ◽  
Stepwise Regression ◽  
Partial Least Squares Regression ◽  
Monitoring Data ◽  
Least Squares Regression ◽  
Security Monitoring ◽  
Optimization Study ◽  
Optimized Model

Both Stepwise Regression (SR) and Partial Least Squares Regression (PLSR) can be applied in data analysis of dam security monitoring, and achieve in fitting and forecasting. However, SR and PLSR models still can be optimized. A variety of programs are studied and compared based on actual dam security monitoring data. The results show that the optimized-model is better in fitting and forecasting the monitoring data.

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