Estimating daily global solar radiation

What is it about?

Solar radiation is a global ecological phenomenon that affects life everywhere. I have created 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 were 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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Why is it important?

Researchers are interested in predicting the amount of light and heat, together or individually, because of its significant impact on the surrounding environment. To exemplify, the effects of light and heat are evident in photosynthesis of plants and in increasing or decreasing tropical and subtropical regions. This is why the Markovian arrival process is adopted in the present study, but with a new statistical method, called the Quartiles-Moment's method, to produce accurate prediction regression models (e.g., nonlinear regression of the cumulative distribution functions) for estimating the daily global solar radiation and the daily maximum temperature. Thus, the multiple nonlinear regression of the joint distribution function of the global solar radiation and the maximum temperature is strictly obtained and compared with the real dataset. On the other hand, in the case of high temperature and low solar radiation, other factors such as environmental pollution or climate change would lead to increasing the temperature of the atmosphere, the notice that helps governments predict such changes and make precautionary solutions to avoid environmental pollution and to take full advantage of solar radiation.