Deriving robust bayesian premiums under bands of prior distributions with applications
Contenido multimedia no disponible por derechos de autor o por acceso restringido. Contacte con la institución para más información.
| Tag | 1 | 2 | Valor |
|---|---|---|---|
| LDR | 00000cab a2200000 4500 | ||
| 001 | MAP20190019132 | ||
| 003 | MAP | ||
| 005 | 20190625124238.0 | ||
| 008 | 190619e20190101gbr|||p |0|||b|eng d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a6 | ||
| 100 | 1 | $0MAPA20190008167$aSánchez-Sánchez, M. | |
| 245 | 0 | 0 | $aDeriving robust bayesian premiums under bands of prior distributions with applications$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 | |
| 773 | 0 | $wMAP20077000420$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 |