Application of principal component analysis–multivariate adaptive regression splines for the simultaneous spectrofluorimetric determination of dialkyltins in micellar media

2013 ◽  
Vol 115 ◽  
pp. 357-363 ◽  
Author(s):  
Jahan B. Ghasemi ◽  
Ehsan Zolfonoun
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Multivariate Adaptive Regression Splines ◽  
Regression Splines ◽  
Micellar Media ◽  
Spectrofluorimetric Determination ◽  
Adaptive Regression ◽  
Adaptive Regression Splines

scholarly journals Comparison of Logistic Regression Model and MARS Using Multicollinearity Data Simulation

2020 ◽  
Vol 4 (1) ◽  
pp. 39
Author(s):  
Ananto Wibowo ◽  
M. Rismawan Ridha
Keyword(s):  
Logistic Regression ◽  
Principal Component ◽  
Multivariate Adaptive Regression Splines ◽  
Predictor Variables ◽  
Regression Splines ◽  
Data Simulation ◽  
Simulation Data ◽  
Adaptive Regression ◽  
Categorical Response ◽  
Adaptive Regression Splines

There are several statistical methods used to model the effect of predictor variables on categorical response variables, namely logistic regression and Multivariate Adaptive Regression Splines (MARS). However, neither MARS nor logistic regression allows multicollinearity on any predictor variables. This study applies the use of both methods to the simulation data with principal component analysis as an improvement in multicollinearity to find out which regression has better performance. The result of the analysis shows that MARS is very powerful in modeling research simulation data. Besides, based on the criteria of the number of significant major components, accuracy, sensitivity, and specificity values, MARS has more appropriate performance than logistic regression.

Determination of Agarwood oil’s significant chemical compounds using principal component analysis

2020 ◽  
Author(s):  
Mohamad Hushnie Haron ◽  
Mohd Nasir Taib ◽  
Nurlaila Ismail ◽  
Nor Azah Mohd Ali ◽  
Saiful Nizam Tajuddin
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Chemical Compounds ◽  
Component Analysis ◽  
Significant Chemical

Prediction of transportation energy demand: Multivariate Adaptive Regression Splines

Energy ◽  
2021 ◽  
Vol 224 ◽  
pp. 120090
Author(s):  
Mohammad Ali Sahraei ◽  
Hakan Duman ◽  
Muhammed Yasin Çodur ◽  
Ecevit Eyduran
Keyword(s):  
Energy Demand ◽  
Multivariate Adaptive Regression Splines ◽  
Regression Splines ◽  
Transportation Energy ◽  
Adaptive Regression ◽  
Adaptive Regression Splines
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