Combinatorial protocol in multiple linear regression/partial least-squares directed rationale for the caspase-3 inhibition activity of isoquinoline-1,3,4-trione derivatives

2010 ◽  
Vol 21 (1-2) ◽  
pp. 169-185 ◽  
Author(s):  
B.K. Sharma ◽  
P. Pilania ◽  
P. Singh ◽  
Y.S. Prabhakar
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Least Squares ◽  
Partial Least Squares ◽  
Caspase 3 ◽  
Inhibition Activity

A multiple linear regression and partial least squares study of flavonoid compounds with anti-HIV activity

2001 ◽  
Vol 541 (1-3) ◽  
pp. 81-88 ◽  
Author(s):  
C.N Alves ◽  
J.C Pinheiro ◽  
A.J Camargo ◽  
M.M.C Ferreira ◽  
R.A.F Romero ◽  
...  
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Least Squares ◽  
Partial Least Squares ◽  
Flavonoid Compounds ◽  
Anti Hiv

scholarly journals Prediction of Lard in Palm Olein Oil Using Simple Linear Regression (SLR), Multiple Linear Regression (MLR), and Partial Least Squares Regression (PLSR) Based on Fourier-Transform Infrared (FTIR)

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Siong Fong Sim ◽  
Min Xuan Laura Chai ◽  
Amelia Laccy Jeffrey Kimura
Keyword(s):  
Fourier Transform ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Least Squares ◽  
Partial Least Squares ◽  
Partial Least Squares Regression ◽  
Palm Olein ◽  
Least Squares Regression ◽  
Simple Linear Regression ◽  
Olein Oil

Fourier-transform infrared (FTIR) offers the advantages of rapid analysis with minimal sample preparation. FTIR in combination with multivariate approach, particularly partial least squares regression (PLSR), has been widely used for adulterant analysis. Limited study has been done to compare PLSR with other regression strategies. In this paper, we apply simple linear regression (SLR), multiple linear regression (MLR), and PLSR for prediction of lard in palm olein oil. Pure palm olein oil was adulterated with lard at different concentrations and subjected to analysis with FTIR. The marker bands distinguishing lard and palm olein oil were determined using Fisher’s weights. The marker regions were then subjected to regression analysis with the models verified based on 100 training/test sets. The prediction performance was measured based on the percentage root mean square error (%RMSE). The absorption bands at 3006 cm−1, 2852 cm−1, 1117 cm−1, 1236 cm−1, and 1159 cm−1 were identified as the marker bands. The bands at 3006 and 1117 cm−1 were found with satisfactory predictive ability, with PLSR demonstrating better prediction yielding %RMSE of 16.03 and 13.26%, respectively.

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