Convergence rate for cross-validatory bandwidth in kernel hazard estimation from dependent samples

Estévez-Pérez, Graciela; Quintela-del-Rı́o, Alejandro; Vieu, Philippe

doi:10.1016/s0378-3758(01)00245-2

Cited by 15 publications

(6 citation statements)

References 25 publications

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“…[32], the bandwidth selected by this method is ''penalized'' by a quantity λ n , that depends on the data, and it improves the results obtained by the cross-validation criterion. This takes the form…”

Section: Kernel Estimation Of the Hazard Functionmentioning

confidence: 99%

Comparative seismic hazard analysis of two Spanish regions

Quintela-del-Rı́o¹

2011

Physica A: Statistical Mechanics and its Applications

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Section: Kernel Estimation Of the Hazard Functionmentioning

confidence: 99%

Comparative seismic hazard analysis of two Spanish regions

Quintela-del-Rı́o¹

2011

Physica A: Statistical Mechanics and its Applications

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“…Cite, for instance, , Roussas (1989), Lecoutre and Ould-Saïd (1993), Estvez et al (2002) and Quintela-del-Rio (2006) for recent references. In all these works the authors consider independent observations or dependent data from time series.…”

Section: Hazard and Conditional Hazardmentioning

confidence: 99%

Consistency rates and asymptotic normality of the high risk conditional for functional data

Rabhi¹,

Keddani

Hammou³

2016

Acta Universitatis Sapientiae, Mathematica

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Abstract. The maximum of the conditional hazard function is a parameter of great importance in seismicity studies, because it constitutes the maximum risk of occurrence of an earthquake in a given interval of time. Using the kernel nonparametric estimates of the first derivative of the conditional hazard function, we establish uniform convergence properties and asymptotic normality of an estimate of the maximum in the context of independence data.

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“…Cite, for instance, Watson. and Leadbetter (1964b), Roussas (1989), Lecoutre and Ould-Saïd (1992), Estévez-Pérez et al (2002) and Quintela-del-Rio (2006) for recent references. In all these works the authors consider independent observations or dependent data from time series.…”

Section: Hazard and Conditional Hazardmentioning

confidence: 99%

“…Also, the hazard function can have several local maxima, indicating the times with the highest risk in a certain period (see the examples in Estévez-Pérez et al (2002)). …”

mentioning

confidence: 99%

Nonparametric estimation of the maximum of conditional hazard function under dependence conditions for functional data

Rabhi¹,

Hammou²,

Djebbouri³

2015

jas

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Abstract. The maximum of the conditional hazard function is a parameter of great importance in statistics, in particular in seismicity studies, because it constitutes the maximum risk of occurrence of an earthquake in a given interval of time. Using the kernel nonparametric estimates based on convolution kernel techniques of the first derivative of the conditional hazard function, we establish the asymptotic behavior of a hazard rate in the presence of a functional explanatory variable and asymptotic normality of the maximum value in the case of a strong mixing process.Résumé. Le maximum ou encore le pointà haut risque d'une fonction de risque conditionnel est un paramètre d'un grand intérêt en statistique, notamment dans l'analyse de risque séismique, car il constitue le risque maximal de survenance d'un tremblement de terre dans un intervalle de temps donné. Au moyen d'estimations non paramétriques basés sur les techniques de noyau de convolution de la première dérivée de la fonction de hasard conditionnel, nousétablissons le comportement asymptotique d'un taux de hasard d'une variable explicative fonctionnelle ainsi que la normalité asymptotique de la valeur maximale pour un processus mélangeant.

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Convergence rate for cross-validatory bandwidth in kernel hazard estimation from dependent samples

Cited by 15 publications

References 25 publications

Comparative seismic hazard analysis of two Spanish regions

Comparative seismic hazard analysis of two Spanish regions

Consistency rates and asymptotic normality of the high risk conditional for functional data

Nonparametric estimation of the maximum of conditional hazard function under dependence conditions for functional data

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