Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Multiregional Demography× | Multistate Life Table× | |
|---|---|---|
| Nyanja | Demografia | Demografia |
| Familia≠ | Process / pipeline | Survival analysis |
| Mwaka wa asili | 1975 | 1975 |
| Mwanzilishi≠ | Andrei Rogers | Andrei Rogers, Robert Schoen and collaborators |
| Aina≠ | Matrix framework for multiregional population dynamics with migration | Nonparametric life table with multiple living states and transitions |
| Chanzo asilia≠ | Rogers, A. (1975). Introduction to Multiregional Mathematical Demography. John Wiley & Sons, New York. ISBN: 9780471730354 | Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 9781557864512 |
| Majina mbadala≠ | Multiregional Population Analysis, Multiregional Life Table, Rogers Multiregional Model | Increment-Decrement Life Table, Multiple-State Life Table, Multistate Demography, Çok Durumlu Yaşam Tablosu |
| Zinazohusiana | 4 | 4 |
| Muhtasari≠ | Multiregional demography extends the classical tools of mathematical demography — the life table, the Leslie matrix, and stable-population theory — from a single closed population to a system of interconnected regions linked by migration. Developed by Andrei Rogers, it tracks people not only by age but by region of residence, modeling birth, death, and interregional movement simultaneously. The result is a unified matrix framework that yields multiregional life tables, projections, and stable regional population shares, making it the foundation for analyzing how migration shapes the size and distribution of populations across space. | The multistate life table, also called the increment-decrement life table, generalizes the ordinary life table to populations that move among several living states — such as healthy and disabled, married and unmarried, or employed and unemployed — as well as the absorbing state of death. Using age-specific transition rates organized in matrices, it tracks the flows of a synthetic cohort among states and yields state-specific expectancies, such as the years a person can expect to spend healthy versus disabled. |
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