Multiple nonlinear regression of the Markovian arrival process for estimating the daily global solar radiation

Abstract

Solar radiation is a global ecological phenomenon that affects life everywhere. In this study, a new statistical method, called the Quartiles-Moment's method, is proposed to estimate the scale and shape parameters of the exponentiated Gumbel maximum distribution (EGMD). The Kolomogorov–Smirnov test and the percentiles of the dataset are thus used to fit the dataset of the daily global solar radiation and the corresponding daily maximum temperature with EGMD. Thence, multiple nonlinear regression of the daily global solar radiation and the corresponding daily maximum temperature are produced and compared with the real dataset accordingly.

Keywords:

• Markovian arrival process
• exponentiated Gumbel maximum distribution
• quartiles-moment's method
• multiple non linear regression

MATHEMATICS SUBJECT CLASSIFICATION:

• 62G05
• 62G32
• 62G08
• 62P12
• 62J02

Acknowledgments

I would like to thank the staff members of the Australian Bureau of Meteorology for providing climate data about Queensland, Australia online. I also thank all the contributing authors in this field of study.

Disclosure statement

No potential conflict of interest was reported by the author.