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Probabilistic Modeling of Monthly Temperature Historical Series in Mossoró, Northeastern Brazil

Author

Listed:
  • 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.

Suggested Citation

  • 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 Nev, 2024. "Probabilistic Modeling of Monthly Temperature Historical Series in Mossoró, Northeastern Brazil," Journal of Agricultural Science, Canadian Center of Science and Education, vol. 10(12), pages 534-534, April.
    • Handle: RePEc:ibn:jasjnl:v:10:y:2024:i:12:p:534
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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