Software Tools for Statistical Analysis of Some Precipitation Characteristics

Abstract

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.