Frequency Analysis of Extreme Events Using the Univariate Beta Family Probability Distributions

• Published in: Applied sciences Vol. 13; no. 7; p. 4640
• Main Authors: Ilinca, Cornel, Anghel, Cristian Gabriel
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.04.2023
• Subjects: Approximation; beta; Case studies; Disaster victims; Distribution (Probability theory); Distribution functions; Expected values; extreme value statistics; Family; Flood frequency; Frequency analysis; frequency estimates; Hydrology; Kurtosis; Legislation; Methods; Outliers (statistics); Parameter estimation; Pearson VI; Pearson XII; Probability; Probability density functions; Skewness; Statistical analysis; Statistical distributions; Statistics; Romania
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app13074640

This manuscript presents three families of distributions, namely the Beta, Beta Prime and Beta Exponential families of distributions. From all the distributions of these families, 14 statistical distributions of three, four and five parameters are presented that have applicability in the analysis of extreme phenomena in hydrology. These families of distributions were analyzed regarding the improvement of the existing legislation for the determination of extreme events, specifically the elaboration of a norm regarding frequency analysis in hydrology. To estimate the parameters of the analyzed distributions, the method of ordinary moments and the method of linear moments were used; the latter conforms to the current trend for estimating the parameters of statistical distributions. The main purpose of the manuscript was to identify other distributions from these three families with applicability in flood frequency analysis compared to the distributions already used in the literature from these families, such as the Log–logistic distribution, the Dagum distribution and the Kumaraswamy distribution. The manuscript does not exclude the applicability of other distributions from other families in the frequency analysis of extreme values, especially since these families were also analyzed within the research carried out in the Faculty of Hydrotechnics and presented in other materials. All the necessary elements for their use are presented, including the probability density functions, the complementary cumulative distribution functions, the quantile functions and the exact and approximate relations for estimating parameters. A flood frequency analysis case study was carried out for the Prigor RiverRiver, to numerically present the proposed distributions. The performance of this distributions were evaluated using the relative mean error, the relative absolute error and the L-skewness–L-kurtosis diagram. The best fit distributions are the Kumaraswamy, the Generalized Beta Exponential and the Generalized Beta distributions, which presented a stability related to both the length of the data and the presence of outliers.