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A generalized binomial exponential 2 distribution: modeling and applications to hydrologic events

机译:广义二项式指数2分布:水文事件的建模和应用

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Developing statistical methods to model hydrologic events is always interesting for both statisticians and hydrologists, because of its importance in hydraulic structures design and water resource planning. Because of this, a flexible 3-parameter generalization of the exponential distribution is introduced based on the binomial exponential 2 (BE2) distribution [2]. The proposed distribution involving the exponential, gamma and BE2 distributions as submodels; and it exhibits decreasing, increasing and bathtub-shaped hazard rates, so it turns out to be quite flexible for analyzing non-negative real life data. Some statistical properties, parameters estimation and information matrix of the distribution are investigated. The proposed distribution, Gumbel, generalized Logistic and other distributions are utilized to model and fit two hydrologic data sets. The distribution is shown to be more appropriate to the data than the compared distributions using the selection criteria: average scaled absolute error, Akaike information criterion, Bayesian information criterion and Kolmogorov-Smirnov statistics. As a result, some hydrologic parameters of the data are obtained such as return level, conditional mean, mean deviation about the return level and the rth moments of order statistics.
机译:对于统计学家和水文学家来说,开发统计方法来模拟水文事件总是很有趣,因为它在水工结构设计和水资源规划中非常重要。因此,基于二项式指数2(BE2)分布[2]引入了指数分布的灵活的3参数概括。提议的分布涉及指数分布,伽马分布和BE2分布作为子模型;而且它呈现出下降,上升和类似浴缸的危险率,因此对于分析非负面的现实生活数据而言,它具有很大的灵活性。研究了分布的一些统计性质,参数估计和信息矩阵。建议的分布,Gumbel,广义Logistic和其他分布可用于对两个水文数据集进行建模和拟合。与使用选择标准的比较分布相比,该分布更适合于数据:平均比例绝对误差,Akaike信息标准,贝叶斯信息标准和Kolmogorov-Smirnov统计。结果,获得了数据的一些水文参数,例如返回水平,条件平均值,关于返回水平的平均偏差和阶次统计量的第一个矩。

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