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Age-Period-Cohort Model×Lee-Carterモデル×
分野人口学人口学
系統Regression modelRegression model
提唱年19831992
提唱者Theodore R. Holford (modern estimable-function formulation)Ronald Lee & Lawrence Carter
種類Regression decomposition of rates into age, period and cohort effectsStochastic mortality forecasting model
原典Holford, T. R. (1983). The estimation of age, period and cohort effects for vital rates. Biometrics, 39(2), 311–324. DOI ↗Lee, R. D., & Carter, L. R. (1992). Modeling and forecasting U.S. mortality. Journal of the American Statistical Association, 87(419), 659–671. DOI ↗
別名APC Model, Age-Period-Cohort Analysis, Holford APC ModelLC Model, Lee-Carter Mortality Model, Singular Value Decomposition Mortality Model, Lee-Carter Ölümlülük Modeli
関連42
概要The age-period-cohort (APC) model decomposes variation in a vital rate — mortality, incidence, fertility — into three temporal dimensions: the age of individuals, the calendar period of observation, and the birth cohort to which they belong. It is the standard framework for asking whether a trend reflects how risk changes with age, contemporaneous period influences affecting all ages at once, or generational effects carried by successive cohorts. Its defining technical challenge is that cohort equals period minus age, an exact linear dependence that makes the three sets of linear effects unidentifiable without further assumptions; Holford's 1983 formulation clarified exactly which quantities can and cannot be estimated.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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ScholarGate手法を比較: Age-Period-Cohort Model · Lee-Carter Model. 2026-06-25に以下より取得 https://scholargate.app/ja/compare