A bootstrap test of independence between three temporal nonhomogeneous Poisson processes and its application to heat wave modeling

Abaurrea, J. (Universidad de Zaragoza) ; Asín, J. (Universidad de Zaragoza) ; Cebrián, A.C. (Universidad de Zaragoza)

Resumen: The main contribution of this work is a bootstrap test to check the independence between temporal nonhomogeneous Poisson processes. The test statistic is based on the close point relation, which adapts the crossed nearest neighbour distance ideas of spatial point processes to the case of nonhomogeneous time point processes. Since it is complicated to obtain the probability distribution of the test statistic under the null hypothesis and the parameters of the processes are usually unknown, the p value is obtained using a parametric bootstrap approach. A simulation study shows that the size of the test is close to the nominal one. The power is analyzed considering three approaches for generating dependent nonhomogeneous processes and different levels of dependence, and satisfactory results are obtained in all cases. Although the test was initially intended for Poisson processes, it can be applied to any type of point process in one dimension which can be simulated. This test is a valuable tool in the validation analysis of common Poisson shock models. For the bivariate case, the process can be decomposed into three independent Poisson processes, and the assumption of independence between them has to be checked. As an application, the joint modeling of the occurrence process of extreme heat events in daily maximum and minimum temperatures is described.

Idioma: Inglés

DOI: 10.1007/s10651-014-0288-1

Año: 2015

Publicado en: ENVIRONMENTAL AND ECOLOGICAL STATISTICS 22, 1 (2015), 127-144
ISSN: 1352-8505

Factor impacto JCR: 0.769 (2015)

Categ. JCR: STATISTICS & PROBABILITY rank: 71 / 123 = 0.577 (2015) - Q3 - T2
Categ. JCR: MATHEMATICS, INTERDISCIPLINARY APPLICATIONS rank: 72 / 101 = 0.713 (2015) - Q3 - T3
Categ. JCR: ENVIRONMENTAL SCIENCES rank: 194 / 225 = 0.862 (2015) - Q4 - T3

Factor impacto SCIMAGO: 0.505 - Environmental Science (miscellaneous) (Q2) - Statistics, Probability and Uncertainty (Q3) - Statistics and Probability (Q3)

Financiación: info:eu-repo/grantAgreement/ES/MEC/CGL2009-09646
Financiación: info:eu-repo/grantAgreement/ES/MMA/ESTCENA 2009-0017

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Estadís. Investig. Opera. (Dpto. Métodos Estadísticos)