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Projekcija pa kohortām un komponentēm×Telpiskās mijiedarbības (gravitācijas) modeļi×
NozareDemogrāfijaTelpiskā analīze
SaimeProcess / pipelineRegression model
Izcelsmes gads20011971
AutorsPreston, Heuveline & GuillotAlan Wilson (entropy-maximizing family)
TipsDemographic projection pipelineModel of flows between spatial origins and destinations
PirmavotsPreston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 978-1-557-86451-2Wilson, A. G. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32. DOI ↗
Citi nosaukumiCohort-Component Method, Component Method of Population Projection, Age-Sex-Specific Population Projection, Kohort-Bileşen Projeksiyonugravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeli
Saistītās34
KopsavilkumsCohort-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.Spatial interaction models predict the volume of flows — migrants, commuters, shoppers, trade, trips — between origins and destinations as a function of the size of each place and the distance or cost separating them. By analogy to Newton's gravity, interaction rises with the 'mass' of origin and destination and falls with separation, and Wilson's 1971 entropy-maximizing family put these models on a rigorous footing for transport, migration, and retail analysis.
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ScholarGateSalīdzināt metodes: Cohort-Component Projection · Spatial Interaction Model. Izgūts 2026-06-18 no https://scholargate.app/lv/compare