Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Proiecția Demografică prin Metoda Cohoartelor și Componentelor× | Modelul Lee-Carter× | |
|---|---|---|
| Domeniu | Demografie | Demografie |
| Familie≠ | Process / pipeline | Regression model |
| Anul apariției≠ | 2001 | 1992 |
| Autorul original≠ | Preston, Heuveline & Guillot | Ronald Lee & Lawrence Carter |
| Tip≠ | Demographic projection pipeline | Stochastic mortality forecasting model |
| Sursa seminală≠ | Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 978-1-557-86451-2 | Lee, R. D., & Carter, L. R. (1992). Modeling and forecasting U.S. mortality. Journal of the American Statistical Association, 87(419), 659–671. DOI ↗ |
| Denumiri alternative | Cohort-Component Method, Component Method of Population Projection, Age-Sex-Specific Population Projection, Kohort-Bileşen Projeksiyonu | LC Model, Lee-Carter Mortality Model, Singular Value Decomposition Mortality Model, Lee-Carter Ölümlülük Modeli |
| Înrudite≠ | 3 | 2 |
| Rezumat≠ | Cohort-Component Projection is the standard demographic method for forecasting future population size and age-sex structure by explicitly tracking births, deaths, and migration for each age-sex cohort across discrete time steps. Systematically formalized in the textbook literature by Preston, Heuveline, and Guillot (2001), the method builds on foundational actuarial and demographic work dating to the early twentieth century and remains the workhorse technique used by national statistical offices and international organizations worldwide. | 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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