Estimation and Diagnostic for a Partially Linear Regression based on an Extension of the Rice Distribution: Accepted: October 2022

J. C. S. Vasconcelos; E. M. M. Ortega; G. M. Cordeiro; J. S. Vasconcelos; M. A. M. Biaggioni

Forthcoming

Estimation and Diagnostic for a Partially Linear Regression based on an Extension of the Rice Distribution

Accepted: October 2022

Authors

J. C. S. Vasconcelos University of São Paulo
E. M. M. Ortega University of São Paulo
G. M. Cordeiro Federal University of Pernambuco
J. S. Vasconcelos Paulista State University
M. A. M. Biaggioni Paulista State University

Keywords:

cubic splines, milk production, regression extensions, simulation study, wood data

Abstract

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.

Downloads

FP_REVSTAT2022_out2

Published

2022-11-07

How to Cite

S. Vasconcelos, J. C., M. Ortega, E. M., Cordeiro, G. M., Vasconcelos, J. S., & M. Biaggioni, M. A. (2022). Estimation and Diagnostic for a Partially Linear Regression based on an Extension of the Rice Distribution: Accepted: October 2022. REVSTAT-Statistical Journal. Retrieved from https://revstat.ine.pt/index.php/REVSTAT/article/view/500