Fitting censored and truncated regression data using the mixture of experts models
Contenido multimedia no disponible por derechos de autor o por acceso restringido. Contacte con la institución para más información.
| Tag | 1 | 2 | Value |
|---|---|---|---|
| LDR | 00000cab a2200000 4500 | ||
| 001 | MAP20230012444 | ||
| 003 | MAP | ||
| 005 | 20231214132334.0 | ||
| 008 | 230613e20231205usa|||p |0|||b|eng d | ||
| 040 | $aMAP$bspa$dMAP | ||
| 084 | $a6 | ||
| 100 | 1 | $0MAPA20190015158$aChai Fung , Tsz | |
| 245 | 1 | 0 | $aFitting censored and truncated regression data using the mixture of experts models$cTsz Chai Fung, Andrei L. Badescu & X. Sheldon Lin |
| 520 | $aThe logit-weighted reduced mixture of experts model (LRMoE) is a flexible yet analytically tractable non-linear regression model. Though it has shown usefulness in modeling insurance loss frequencies and severities, model calibration becomes challenging when censored and truncated data are involved, which is common in actuarial practice. In this article, we present an extended expectationconditional maximization (ECM) algorithm that efficiently fits the LRMoE to random censored and random truncated regression data. The effectiveness of the proposed algorithm is empirically examined through a simulation study. Using real automobile insurance data sets, the usefulness and importance of the proposed algorithm are demonstrated through two actuarial applications: individual claim reserving and deductible ratemaking | ||
| 650 | 4 | $0MAPA20080579258$aCálculo actuarial | |
| 650 | 4 | $0MAPA20080593063$aRegresión no lineal | |
| 650 | 4 | $0MAPA20080568085$aBases de datos | |
| 650 | 4 | $0MAPA20080578848$aAnálisis de datos | |
| 650 | 4 | $0MAPA20080553128$aAlgoritmos | |
| 700 | 1 | $0MAPA20210030147$aBadescu, Andrei L. | |
| 700 | 1 | $0MAPA20170014539$aSheldon Lin, X. | |
| 773 | 0 | $wMAP20077000239$g05/12/2022 Tomo 26 Número 4 - 2022 , p. 496-520$x1092-0277$tNorth American actuarial journal$dSchaumburg : Society of Actuaries, 1997- | |
| 856 | 0 | 0 | $yMÁS INFORMACIÓN$u mailto:centrodocumentacion@fundacionmapfre.org?subject=Consulta%20de%20una%20publicaci%C3%B3n%20&body=Necesito%20m%C3%A1s%20informaci%C3%B3n%20sobre%20este%20documento%3A%20%0A%0A%5Banote%20aqu%C3%AD%20el%20titulo%20completo%20del%20documento%20del%20que%20desea%20informaci%C3%B3n%20y%20nos%20pondremos%20en%20contacto%20con%20usted%5D%20%0A%0AGracias%20%0A |