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CONFIDENCE INTERVALS OF QUANTILE FOR THE GENERALIZED LOGISTIC DISTRIBUTION

机译:普通物流分布量的置信区间

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The generalized logistic (GL) distribution has been widely used for frequency analysis because its quantile estimate is unbounded above unless the shape parameter is positive. However, there is a little study related to the confidence intervals that indicate the prediction accuracy of distribution for the GL distribution. In this paper, the estimation of the confidence intervals of quantiles for the GL distribution is presented based on the method of moments (MOM), maximum likelihood (ML), and probability weighted moments (PWM) and the asymptotic variances of each quantile estimator are derived as functions of the sample sizes, return periods, and parameters.
机译:广义逻辑(GL)分布已广泛用于频率分析,因为除非形状参数是阳性的,否则其定量估计是未绑定的。然而,有一些与表明GL分布分布预测准确性的置信区间有关的研究。在本文中,基于片刻(MOM),最大似然(ML)和概率加权时刻(PWM)的方法介绍了GL分布的量级置信区间的估计,并且每个分位数估计器的渐近差异是作为样本大小,返回周期和参数的函数派生。

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