A quantitative comparison of stochastic mortality models on Italian population data

DOI10.1016/j.csda.2017.03.012zbMath1464.62036DBLPjournals/csda/CarforaCO17OpenAlexW2595882584WikidataQ58160074 ScholiaQ58160074MaRDI QIDQ1654277

Y. Aharonov

Publication date: 7 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2017.03.012

zbMATH Keywords

demographyforecastingcohort effectLee-Carter modelgoodness of fitfunctional data models

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Functional data analysis (62R10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Mathematical geography and demography (91D20)

Uses Software

• Demography
• gnm
• MortalitySmooth
• Human Mortality
• ilc

Cites Work

• Modeling and Forecasting U.S. Mortality
• Robustness and convergence in the Lee-Carter model with cohort effects
• The mortality of the Italian population: smoothing techniques on the Lee-Carter model
• Evaluating the goodness of fit of stochastic mortality models
• Robust forecasting of mortality and fertility rates: a functional data approach
• Modelling and forecasting mortality in Spain
• A cohort-based extension to the Lee-Carter model for mortality reduction factors
• The Analysis of Two-Way Functional Data Using Two-Way Regularized Singular Value Decompositions
• Lee–Carter Mortality Forecasting: A Parallel Generalized Linear Modelling Approach for England and Wales Mortality Projections
• On fitting generalized linear and non-linear models of mortality
• Smoothing and forecasting mortality rates
• A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States
• A General Procedure for Constructing Mortality Models

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