Compare Estimate Methods of Parameter to Scheffʼe Mixture Model By Using Generalized Inverse and The Stepwise Regression procedure for Treatment Multicollinearity Problem
DOI:
https://doi.org/10.33095/jeas.v24i109.1560Keywords:
mixture models, variance inflation factor, L-Pseudo component, generalized inverse, Stepwise Regression procedure, mean absolute percentage errorAbstract
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 matrix of 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).
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