Reparameterized extended Maxwell regression: Properties, estimation and application

Abstract

We propose a reparameterized regression for the median of an extended Maxwell distribution that can be used when the response variable has a positive support. We obtain some structural properties of the distribution. The parameter estimates are obtained by maximum likelihood and Bayesian methods. Some influence measures and quantile residuals are defined. Several Monte Carlo simulations are reported for inference purposes. The new regression is applied to an experimental data set.

Keywords:

• Bayesian inference
• experimental data
• likelihood inference
• median
• regression model

Additional information

Funding

The research of this paper was supported by grant from Brazilian agencies (CAPES and CNPq). CNPq Scholarship - Brazil (166774/2020-0).