Compare Estimate Methods of Parameter to Scheffé Mix Models by Using Generalized Inverse and the Stepwise Regression Procedure for Treatment Multicollinearity Problem

Authors

• Dejela I. Mahdi, Department of Statistics, College of Administration and Economics, University of Baghdad, Iraq
• Hala Salman Farhan, Ministry of Higher Education and Scientific Research / Studies, Planning and Follow-up directorate

Abstract

Mixture experiments are response variables based on the proportions of component for this mixture. In our research we will compare the scheffʼe model with the kronecker model for the mixture experiments, especially when the experimental area is restricted. Because of the experience of the mixture of high correlation problem and the problem of multicollinearity between the explanatory variables, which has an effect on the calculation of the Fisher information matrixof the regression model. to estimate the parameters of the mixture model, we used the (generalized inverse ) And the Stepwise Regression procedure, as well as the use of the( Variance Inflation Factor) (VIF) scale to demonstrate the high variances in both models, as well as the use of the (L-Pseudo component) , by Using the R-language simulation To compare them. with critical for compare mean absolute percentage error (MAPE).

DOI

10.33095/jeas.v24i109.1560

Subject Area

Statistical

First Page

472

Last Page

485

Recommended Citation

Mahdi, D. I., & Farhan, H. S. (2018). Compare Estimate Methods of Parameter to Scheffé Mix Models by Using Generalized Inverse and the Stepwise Regression Procedure for Treatment Multicollinearity Problem. Journal of Economics and Administrative Sciences, 24(109), 472-485. https://doi.org/10.33095/jeas.v24i109.1560