The
fitting of the generalized distribution

Pareto join to declustering methods to

analyze to dataset of mean daily flow of

Artemis station, Piracicaba, São Paulo, Brazil

Renato Rodrigues SILVA[1]

Silvio Sandoval ZOCCHI^{1}

§ ABSTRACT:** **One of the most used methodologies in the context of the extreme value
theory is the fitting of the generalized
distribution Pareto to data exceedances over a threshold and the fitting of
generalized extreme value distribution. However, to fit the generalized Pareto distribution to a dataset, it must consider the data is a
sequence independent and having a common distribution that it is usually an
unrealistic assumption. An way of to solve this problem is to use methods of
declustering propose by Leadbetter et al. (1989), that in general identify
groups of ocorrence of extreme flow for after fitting of the generalized
distribution Pareto to maximum of the groups. In this work, was mades the fit generalized distribution Pareto and expoencial distribution, particular case
of GP, join to declustering methods to dataset mean daily flow of Artemis station, Piracicaba, SP, Brazil
and after was compared the estimates the return levels of 5, 10, 50 and 100
years. Concludes the intervals estimates of return levels of 50 and 100 years
obtained through the fitting the exponencial distribution are more precision
than obtained through the fitting the generalized Pareto distribution.

§ KEYWORDS:** **Generalized distribution Pareto;
generalized extremes values distribution; return levels.

[1] Departamento Ciências Exatas, Escola Superior de Agricultura ``Luiz de Queiroz", Universidade de São Paulo, Caixa Postal 9, CEP 13418-900 , Piracicaba, São Paulo, Brasil. E-mail: rrsilva@esalq.usp.br / sszocchi@esalq.usp.br