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Keyfitz Entropy×Μοντέλο Lee-Carter×
ΠεδίοΔημογραφίαΔημογραφία
ΟικογένειαProcess / pipelineRegression model
Έτος προέλευσης19771992
ΔημιουργόςNathan KeyfitzRonald Lee & Lawrence Carter
ΤύποςElasticity of life expectancy to proportional mortality change / lifespan dispersion measureStochastic mortality forecasting model
Θεμελιώδης πηγήKeyfitz, N. (1977). Applied Mathematical Demography. John Wiley & Sons, New York. ISBN: 9780471473503Lee, R. D., & Carter, L. R. (1992). Modeling and forecasting U.S. mortality. Journal of the American Statistical Association, 87(419), 659–671. DOI ↗
Εναλλακτικές ονομασίεςLife-Table Entropy, Keyfitz-Leser Entropy, Entropy of the Survival CurveLC Model, Lee-Carter Mortality Model, Singular Value Decomposition Mortality Model, Lee-Carter Ölümlülük Modeli
Συναφείς42
ΣύνοψηKeyfitz's entropy, usually written H, is a dimensionless summary of a life table that measures how sensitive life expectancy is to a proportional change in mortality, and equivalently how unequal the distribution of ages at death is. Introduced by Nathan Keyfitz, it is the elasticity of life expectancy at birth with respect to the force of mortality: an H near one means deaths are spread across all ages so that reducing mortality everywhere lengthens life proportionally, while an H near zero means deaths are concentrated near the maximum lifespan so further mortality reductions yield little gain. It bridges the demography of survival and the broader study of lifespan inequality.The Lee-Carter model is a stochastic framework for modeling and forecasting age-specific mortality rates, introduced by Ronald Lee and Lawrence Carter in their landmark 1992 paper. It decomposes the logarithm of age-specific death rates into an age pattern of mortality, a time-varying index of mortality level, and an age-specific sensitivity of that index, then forecasts the time index using ARIMA time-series methods to generate probabilistic mortality projections.
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ScholarGateΣύγκριση μεθόδων: Keyfitz Entropy · Lee-Carter Model. Ανακτήθηκε στις 2026-06-25 από https://scholargate.app/el/compare