Estimation and Diagnostic for a Partially Linear Regression based on an Extension of the Rice Distribution
Accepted: October 2022
Keywords:cubic splines, milk production, regression extensions, simulation study, wood data
We introduce an extension of the Rice distribution and estimate its parameters by maximum likelihood. We define two regressions based on this extended distribution to model volumetric shrinkage of the wood and milk production. The performance of the parameter estimators is investigated infinite samples using Monte Carlo simulations. Also, we propose the quantile residuals for the regression models whose empirical distribution is close to normality. The usefulness of the new regressions is proved empirically through two applications to agricultural data.
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