Linganisha mbinu

	Makadirio ya Idadi ya Watu kwa Njia ya Vikundi-Vijenzi	Mfumo wa Lee-Carter	Uchanganuzi wa Jedwali la Maisha
Nyanja	Demografia	Demografia	Demografia
Familia	Process / pipeline	Regression model	Survival analysis
Mwaka wa asili	2001	1992	1984
Mwanzilishi	Preston, Heuveline & Guillot	Ronald Lee & Lawrence Carter	Demographic/actuarial tradition; Chiang
Aina	Demographic projection pipeline	Stochastic mortality forecasting model	Age-structured mortality estimator
Chanzo asilia	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.	Chiang, C. L. (1984). The Life Table and Its Applications. Robert E. Krieger Publishing. ISBN: 978-0-89874-565-2
Majina mbadala	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	Mortality Table, Actuarial Table, Survival Table, Yaşam Tablosu
Zinazohusiana	3	2	3
Muhtasari	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.	A life table is a systematic, age-structured summary of the mortality experience of a population. It traces a hypothetical cohort of births — conventionally 100,000 — through successive age intervals, recording how many survive, how many die, and how many person-years are lived at each interval. The method was formalized in its modern probabilistic form by Chiang (1984), synthesizing centuries of actuarial and demographic practice into a rigorous statistical framework applicable to human and biological populations alike.