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Software Tools for Statistical Analysis of Some Precipitation Characteristics

机译:一些降水特征的统计分析软件工具

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The paper presents the design and implementation of software tools for statistical analysis of the real data based on the assumptions that empirical distribution can be approximated by generalized negative binomial (GNB) or generalized gamma (GG) families. Models based on GG distributions are widely applied in such practical problems as processing of synthetic-aperture radar images and speech signals, hydrological analysis and optical communications. In this paper, the GNB distributions are considered as a mixed Poisson law with the mixing GG distribution. This family could provide better fit with the different statistical data than classical negative binomial distributions that have been successfully used for analysis of precipitation events earlier. The parameter estimation is implemented using a functional approach, so approximations by different types of distributions are compared in sense of different metrics. The results of application of the implemented software tools are demonstrated on the example of the Potsdam precipitation events.
机译:本文介绍了对实际数据的统计分析的软件工具的设计和实现,基于经验分布可以通过广义负二进制(GNB)或广义γ(GG)家族近似的假设。基于GG分布的模型广泛应用于合成孔径雷达图像和语音信号,水文分析和光通信的处理中的实际问题。在本文中,GNB分布被认为是混合GG分布的混合泊松法。该家庭可以更好地提供不同于古典负二项份分布的不同统计数据,这些分布已经成功地用于分析降水事件。参数估计使用功能方法来实现,因此在不同度量的意义上比较了不同类型的分布的近似。在Potsdam降水事件的示例上证明了所实施的软件工具的应用结果。

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