Salīdzināt metodes

	Lī-Kārtera modelis	ARIMA (autoregresīvais integrētais slīdošā vidējā) modelis	Dzīvildzes analīze
Nozare	Demogrāfija	Ekonometrija	Demogrāfija
Saime	Regression model	Regression model	Survival analysis
Izcelsmes gads	1992	2015	1984
Autors	Ronald Lee & Lawrence Carter	Box & Jenkins (Box-Jenkins methodology)	Demographic/actuarial tradition; Chiang
Tips	Stochastic mortality forecasting model	Univariate time-series model	Age-structured mortality estimator
Pirmavots	Lee, R. D., & Carter, L. R. (1992). Modeling and forecasting U.S. mortality. Journal of the American Statistical Association, 87(419), 659–671.	Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021	Chiang, C. L. (1984). The Life Table and Its Applications. Robert E. Krieger Publishing. ISBN: 978-0-89874-565-2
Citi nosaukumi	LC Model, Lee-Carter Mortality Model, Singular Value Decomposition Mortality Model, Lee-Carter Ölümlülük Modeli	Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli	Mortality Table, Actuarial Table, Survival Table, Yaşam Tablosu
Saistītās	2	5	3
Kopsavilkums	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.	ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).	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.