In this paper we mirror the framework of generalized (non-)linear models to define the family of generalized age-period-cohort stochastic mortality models which encompasses the vast majority of stochastic mortality projection models proposed to date, including the well-known Lee-Carter and Cairns-Blake-Dowd models. We also introduce the R package StMoMo which exploits the unifying framework of the generalized age-period-cohort family to provide tools for fitting stochastic mortality models, assessing their goodness of fit and performing mortality projections. We illustrate some of the capabilities of the package by performing a comparison of several stochastic mortality models applied to the England and Wales population.
StMoMo: Stochastic Mortality Modeling in R / Andres, Villegas; Millossovich, Pietro; Vladimir, Kaishev. - In: JOURNAL OF STATISTICAL SOFTWARE. - ISSN 1548-7660. - ELETTRONICO. - 84:3(2018), pp. 1-38. [10.18637/jss.v084.i03]
StMoMo: Stochastic Mortality Modeling in R
MILLOSSOVICH, PIETRO;
2018-01-01
Abstract
In this paper we mirror the framework of generalized (non-)linear models to define the family of generalized age-period-cohort stochastic mortality models which encompasses the vast majority of stochastic mortality projection models proposed to date, including the well-known Lee-Carter and Cairns-Blake-Dowd models. We also introduce the R package StMoMo which exploits the unifying framework of the generalized age-period-cohort family to provide tools for fitting stochastic mortality models, assessing their goodness of fit and performing mortality projections. We illustrate some of the capabilities of the package by performing a comparison of several stochastic mortality models applied to the England and Wales population.| File | Dimensione | Formato | |
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