Detalhes bibliográficos
| Ano de defesa: |
2020 |
| Autor(a) principal: |
SILVA, Luciano Pereira da
 |
| Orientador(a): |
SILVA, Frank Sinatra Gomes da |
| Banca de defesa: |
VASCONCELOS, Josimar Mendes de |
| Tipo de documento: |
Dissertação
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal Rural de Pernambuco
|
| Programa de Pós-Graduação: |
Programa de Pós-Graduação em Biometria e Estatística Aplicada
|
| Departamento: |
Departamento de Estatística e Informática
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://www.tede2.ufrpe.br:8080/tede2/handle/tede2/8764
|
Resumo: |
Rain is an element that causes many concerns, because its intensity and frequency of occurrence, can cause harmful effects to society, the rain of a given location can be estimated, in probabilistic terms, by theoretical distribution models adjusted to a historical series. Precipitation data from the state of Pernambuco were used, formed by 133 monthly time series distributed over the entire state during the period from 1950 to 2012. Adherences of Probability distributions were analyzed: exponential, gamma,beta, lognormal, Weibull, normal, Gumbel Marshall-Olkin, log-logistics, exponentiated log-logistics, based on the Kolmogorov-Smirnov test at the 5% significance level . The distributions with less rejection during the adherence test were Weibull, gamma and beta, october had the lowest number of distributions considered adequate to model monthly precipitation and in march more than 99% of the pluviometric stations had some adequate probabilistic distribution to model precipitation monthly. The Weibull distribution was the best suited to model monthly precipitation. |
