CvmortalityMult: Cross-Validation for Multi-Population Mortality Models

This article presents the CvmortalityMult R package, a novel tool designed for modelling, forecasting and evaluating mortality models for several populations. The package facilitates the fitting and forecasting of multipopulation mortality models, providing accurate projections in an increasingly interconnected world characterized by minimal or no borders between countries. By incorporating different cross-validation (CV) techniques, the package allows for the assessment of the forecasting accuracy of multipopulation mortality models for specific countries or regions within a country. Through an empirical application to Spanish regions, we demonstrate the efficacy and simplicity of the CvmortalityMult R package in selecting and evaluating multipopulation mortality models. By providing accessible tools for mortality modelling, forecasting and testing, this package stands out as a valuable resource for advancing the understanding and forecasting of mortality trends across diverse populations. Its contributions extend to enhancing decision-making in critical fields such as life insurance, public health, and pension plan sustainability.

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Publication Details

Journal
The R Journal
Published
2025-09-24
DOI
https://doi.org/10.32614/rj-2025-018
Primary Topic
Insurance, Mortality, Demography, Risk Management
Type
article
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article

CvmortalityMult: Cross-Validation for Multi-Population Mortality Models

The R Journal
Insurance, Mortality, Demography, Risk Management
article

CvmortalityMult: Cross-Validation for Multi-Population Mortality Models

article en

Abstract

This article presents the CvmortalityMult R package, a novel tool designed for modelling, forecasting and evaluating mortality models for several populations. The package facilitates the fitting and forecasting of multipopulation mortality models, providing accurate projections in an increasingly interconnected world characterized by minimal or no borders between countries. By incorporating different cross-validation (CV) techniques, the package allows for the assessment of the forecasting accuracy of multipopulation mortality models for specific countries or regions within a country. Through an empirical application to Spanish regions, we demonstrate the efficacy and simplicity of the CvmortalityMult R package in selecting and evaluating multipopulation mortality models. By providing accessible tools for mortality modelling, forecasting and testing, this package stands out as a valuable resource for advancing the understanding and forecasting of mortality trends across diverse populations. Its contributions extend to enhancing decision-making in critical fields such as life insurance, public health, and pension plan sustainability.

The R JournalVol. 17(2)
Universidad de Alcalá (ES), Universitat Politècnica de València (ES)
Decent work and economic growth
Openalex Percentile: Top 27%
Insurance, Mortality, Demography, Risk Management
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