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Keyfitz Entropy×Модел на Лий-Картър×
ОбластДемографияДемография
СемействоProcess / pipelineRegression model
Година на възникване19771992
СъздателNathan KeyfitzRonald Lee & Lawrence Carter
ТипElasticity of life expectancy to proportional mortality change / lifespan dispersion measureStochastic mortality forecasting model
Основополагащ източникKeyfitz, 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 ↗
Други названияLife-Table Entropy, Keyfitz-Leser Entropy, Entropy of the Survival CurveLC Model, Lee-Carter Mortality Model, Singular Value Decomposition Mortality Model, Lee-Carter Ölümlülük Modeli
Свързани42
РезюмеKeyfitz'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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ScholarGateСравнение на методи: Keyfitz Entropy · Lee-Carter Model. Извлечено на 2026-06-25 от https://scholargate.app/bg/compare