Probabilistic Modeling of Monthly Temperature Historical Series in Mossoró, Northeastern Brazil
- Janilson Pinheiro de Assis
- Roberto Pequeno de Sousa
- Ben Deivide de Oliveira Batista
- Paulo César Ferreira Linhares
- Eudes de Almeida Cardoso
- José Aluisio de Araújo Paula
- Ariana Morais Neves
Abstract
We fitted the following seven distribution probabilities to the data of monthly average temperature in Mossoró, northeastern Brazil: Normal, Log-Normal, Beta, Gamma, Log-Pearson (Type III), Gumbel, and Weibull. To assess the goodness of fit the empirical distributions to the theoretical distribution, we applied the tests of Kolmogorov-Smirnov, Chi-square, Cramer-von Mises, Anderson-Darling, Kuiper, and Logarithm of Maximum Likelihood, at 10% of probability. The temperature series were obtained from 1970 to 2007. The Normal distribution provided the best fit to the historical series of average monthly temperature. Although the Kolmogorov-Smirnov test showed a very high level of approval, which generated some uncertainty regarding the test criteria, it is the more recommended to studies with approximately symmetric data and small series.
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- DOI:10.5539/jas.v10n12p534
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