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Deriving robust bayesian premiums under bands of prior distributions with applications

Recurso electrónico / Electronic resource
Registro MARC
Tag12Valor
LDR  00000cab a2200000 4500
001  MAP20190019132
003  MAP
005  20190625124238.0
008  190619e20190101gbr|||p |0|||b|eng d
040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
084  ‎$a‎6
1001 ‎$0‎MAPA20190008167‎$a‎Sánchez-Sánchez, M.
24500‎$a‎Deriving robust bayesian premiums under bands of prior distributions with applications‎$c‎M. Sánchez-Sánchez... [et al.]
300  ‎$a‎22 p.
520  ‎$a‎We study the propagation of uncertainty from a class of priors introduced by Arias-Nicolás et al. [(2016) Bayesian Analysis, 11(4), 11071136] to the premiums (both the collective and the Bayesian), for a wide family of premium principles (specifcally, those that preserve the likelihood ratio order). The class under study reflects the prior uncertainty using distortion functions and fulfills some desirable requirements: elicitation is easy, the prior uncertainty can be measured by different metrics, and the range of quantities of interest is easily obtained from the extremal members of the class. We illustrate the methodology with several examples based on different claim counts models.
650 4‎$0‎MAPA20080602437‎$a‎Matemática del seguro
650 4‎$0‎MAPA20100065242‎$a‎Teorema de Bayes
650 4‎$0‎MAPA20080586447‎$a‎Modelo estocástico
7730 ‎$w‎MAP20077000420‎$t‎Astin bulletin‎$d‎Belgium : ASTIN and AFIR Sections of the International Actuarial Association‎$x‎0515-0361‎$g‎01/01/2019 Volumen 49 Número 1 - enero 2019 , p. 147-168