Daily global solar radiation (DGSR) is a renewable energy source that cannot be depleted. Many researchers have used the sample method to collect the dataset of DGSR to obtain the statistical characteristics of the population. However, since this is difficult, descriptive statistics and statistical inference became the primary objective of obtaining the characteristics of the statistical population. In this study, a statistical model combined with generalized extreme value (GEV) distribution is proposed to represent the dataset of DGSR. The moments method, the Kolmogorov-Smirnov test, and the properties of GEV were performed to estimate the parameters of GEV and check the validity of the estimated parameters with the actual dataset of DGSR. Nonlinear regression and multiple nonlinear regression of GEV with its corresponding days during a year were produced. Eventually, a flowchart was designed to obtain the close probability distribution of the DGSR.
