Modeling Biased Fineness and Maturity Results

Abstract

In an earlier paper, our classical models study included simulations to explain the variability in coefficients of determination (R²) between fineness and maturity, micronaire and fineness, and micronaire and maturity of cotton. Subsequently, we emphasized the derivation and testing of three diagnostic models to enhance the R² and provide information about the analytical quality (accuracy) of the results. In this paper, the theory of biased fineness and maturity measures is introduced and effects on the relationships with micronaire are simulated. Error functions based on Lord's micronaire model are derived to express biased results relative to the unbiased values. The simulations include three case studies in order of increasing complexity: bias varies linearly with micronaire, bias is nonlinear with micronaire, and random error is added to the bias. Classical and diagnostic model plots of the simulated unbiased and biased data are presented in detail to readily determine differences in the relationships.

Keywords

cotton fineness maturity bias modeling Lord's model

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