Multiple nonlinear regression of the Markovian arrival process for estimating the daily global solar radiation |
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Authors: | Mohammed El Genidy |
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Affiliation: | 1. Department of Mathematics and Computer Science, Faculty of Science, Port Said University, Port Said, Egyptdrmmg2016@yahoo.com |
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Abstract: | AbstractSolar 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. |
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Keywords: | Markovian arrival process exponentiated Gumbel maximum distribution quartiles-moment's method multiple non linear regression |
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