Stochastic modeling using the generalized distribution of extreme values and LH moments: an approach through free software R
DOI:
https://doi.org/10.35819/remat2021v7i2id5106Keywords:
GEV, extreme values, free software R, stochastic modelingAbstract
Generalized Extreme Value (GEV) distribution is used to modeling extreme natural events, such as rainfall, floods, wind speed and temperature. An important issue for GEV use is the choice of parameter estimation methodology. The commonly used methodologies are maximum likelihood and conventional moments. However, studies indicate that such methodologies do not always produce a reliable estimate of GEV parameters. In this sense, it is interesting to use LH moments, as they better characterize the upper tail of the distribution due to the emphasis given to the highest observed values. Nevertheless, there are no computational routines developed for GEV use combined with LH moments in free software. Therefore, this research aimed at developing a computational routine in free software R for stochastic modeling through GEV, using LH moments to estimate its parameters and verify goodness-of-fit. Maximum annual flow data available in the literature was used to demonstrate the applicability of the computational routine. This research contributes to disseminate the use of LH moments and facilitate stochastic modeling of extreme environmental events.
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