The software EXTRASTAR (EXTRemes Abacus for STAtistical Regionalization) is here proposed. It can represent a useful and quick tool for both regional and at-site statistical analyses of Annual Maxima (AM) time series. The innovative aspects (compared to other algorithms/softwares) are: 1) an easy comparison of sample skewness of several observed series with pre-determined Monte Carlo Prediction Intervals (depending on sample size) from hypothesized probability distributions, for obtaining a first important indication about possible clusters and regional values for some parameters, which can be afterward refined (if deemed as necessary) with specific and more complex algorithms/softwares proposed in literature; 2) for at-site analyses, the possibility to benefit from calibration of one function for some parameters of the others (thus significantly reducing the computational costs). EXTRASTAR was tested with the daily AM series for the Italian rain-gauge network, by implementing EV1, GEV and TCEV distributions.
A user-friendly software for modelling extreme values: EXTRASTAR (EXTRemes Abacus for STAtistical Regionalization) / De Luca, Dl; Napolitano, F. - In: ENVIRONMENTAL MODELLING & SOFTWARE. - ISSN 1364-8152. - 161:(2023). [10.1016/j.envsoft.2023.105622]
A user-friendly software for modelling extreme values: EXTRASTAR (EXTRemes Abacus for STAtistical Regionalization)
De Luca, DL
;Napolitano, F
2023
Abstract
The software EXTRASTAR (EXTRemes Abacus for STAtistical Regionalization) is here proposed. It can represent a useful and quick tool for both regional and at-site statistical analyses of Annual Maxima (AM) time series. The innovative aspects (compared to other algorithms/softwares) are: 1) an easy comparison of sample skewness of several observed series with pre-determined Monte Carlo Prediction Intervals (depending on sample size) from hypothesized probability distributions, for obtaining a first important indication about possible clusters and regional values for some parameters, which can be afterward refined (if deemed as necessary) with specific and more complex algorithms/softwares proposed in literature; 2) for at-site analyses, the possibility to benefit from calibration of one function for some parameters of the others (thus significantly reducing the computational costs). EXTRASTAR was tested with the daily AM series for the Italian rain-gauge network, by implementing EV1, GEV and TCEV distributions.File | Dimensione | Formato | |
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