principal component regression (PCR)
Application of Principal Component Regression with Dummy Variable in Statistical Downscaling to Forecast Rainfall
... lag was determined using the cross-correlation function. However, GCM data of 64 grids showed multicollinearity problem. This problem was solved by principal component regression (PCR), but the PCR ...
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A Principal Component Regression Approach for Estimating Ventricular Repolarization Duration Variability
... Ventricular repolarization duration (VRD) is affected by heart rate and autonomic control, and thus VRD varies in time in a similar way as heart rate. VRD variability is commonly assessed by determining the time ...
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SPECTROMETRIC DETERMINATION OF SOME HEAVY METALS IN COSMETIC PRODUCTS FOUND BY PRINCIPAL COMPONENT REGRESSION AND PARTIAL LEAST SQUARES METHODS
... used regression method in chemometrics ...with principal component regression (PCR) calibration for a PLS calibration it is known that information from the concentration values is introduced ...
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Batch-to-Batch Iterative Learning Control for End-Point Qualities Based on Kernel Principal Component Regression Model
... kernel principal component regression ...and principal component regression (PCR) model based ILCs are also made in the ...
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Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression
... traditional principal component regression (PCR) as well as probabilistic principal component regression (pPCR) that as- sumes the empirical principal components are a ...
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Analysis of Principal Component Regression Equations of Air Transportation and Local Economy: Taking Tianjin as an Example
... multiple regression model are highly ...multiple regression model with correlated predictors can indicate how well the entire bundle of pre- dictors predicts the outcome variable, but it may not give valid ...
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Optimal Choice of Cotton Subsidy Mode in China—Empirical Study Based on Principal Component Regression
... Adopt principal component regression for researching the optimal subsidy mode of cotton production in China. The result indicates that, from the perspective of economic stimulatory effect, the ...
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Unified Discrete Wavelet Transform with Ridge Regression and Principal Component Regression to Predict Concentration of Gingerol Compound in Ginger Crop
... conventional regression is not ...Ridge Regression and Principal Component Regression have been adopted in this paper to predict con- centration of gingerol, and it showed a promising ...
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Multi adaptive Natural Language Generation using Principal Component Regression
... combines Principal Com- ponent Analysis (PCA) (Jolliffe, 1986) with lin- ear ...the principal compo- nents, in our case, the factors that contribute the most to the ...Then, regression is applied to ...
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PREDICTIVE COMPARATIVE QSAR ANALYSIS OF AS NITROTRIAZOLE- AND IMIDAZOLE-BASED AMIDES DERIVATIVES MYCOBACTERIUM TUBERCULOSIS H37RV INHIBITORS
... Principal Component Regression (PCR) is a regression technique that uses principal component analysis(PCA) when evaluating regression ...called principal components ...
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Principal Component and Multiple Regression Analysis for Steel Fiber Reinforced Concrete (SFRC) Beams
... linear regression model is a typically form of simple models where more than one independent variables are ...The principal component regression (PCR), special types of regression, can ...
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New approaches in estimating linear regression model parameters in the presence of multicollinearity and outliers
... linear regression models, the ordinary least squares (OLS) method has been the most popular technique for estimating parameters of model due to its optimal properties and ease of ...The Principal ...
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1. Simultaneous determination of drugs used for chronic active gastritis disease by chemometric methods
... Abstract- The spectrophotometric-chemometric analysis of clarithromycin amoxicillin and lansoprazole that are used for the eradication of Helicobacter pylori (HP) was analysis without any prior reservation. The used ...
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SIMULTANEOUS SPECTROPHOTOMETRIC DETERMINATION OF RABEPRAZOLE SODIUM AND DOMPERIDONE MALEATE IN CAPSULES BY CHEMOMETRIC METHODS
... (ILS), principal component regression (PCR) and partial least- squares (PLS) are started to apply to the analysis of the analytical data obtained in all the instrumentations 16-17 ...
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Soil Quality Assessment By Near Infrared Spectroscopy: Predicting Ph And Soil Organic Carbon
... using principal component regression (PCR) and partial least square regression (PLS) followed by leave one out cross validation (LOOCV) ...
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Statistical Prediction Of Laser Generation For A High-Powered Copper Bromide Vapor Laser
... and principal component regression (PCR) [5, ...of principal component analysis (PCA) ...multiple regression analysis, which is known as PCR. The regression method ...
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Comparative qsar analysis of histone deacetylase 6 (hdac6) inhibitors as anti cancer agents
... Linear Regression (MLR), Principal Component Regression (PCR) besides Partial east Squares regression (PLS) methods, in addition to a 3D QSAR model which was developed ...linear ...
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CHEMOMETRIC ANALYSIS OF PARACETAMOL AND METACLOPROMIDE IN BINARY DRUG COMBINATIONS
... INTRODUCTION: Paracetamol is used as an analgesic in medicines, and metaclopromide is also used as medicinal medicines. These two drugs have obtained mixture spectra with certain persons or with certain drugs, ...
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2D QSAR Studies on 1, 4 dihydropyridines as Ca++ Channel Blockers
... linear regression (MLR), Principal component regression (PCR) and Partial Least Squares regression (PLR) analysis were generated to find out correlation between the physicochemical ...
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A Comparative Study On Some Methods For Handling Multicollinearity Problems
... In regression, the objective is to explain the variation in one or more response variables, by associating this variation with proportional variation in one or more explanatory ...in regression analysis. ...
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