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Projekcija pa kohortām un komponentēm×Radiācijas mobilitātes un migrācijas modelis×Telpiskās mijiedarbības (gravitācijas) modeļi×
NozareDemogrāfijaTelpiskā analīzeTelpiskā analīze
SaimeProcess / pipelineRegression modelRegression model
Izcelsmes gads200120121971
AutorsPreston, Heuveline & GuillotFilippo Simini et al.Alan Wilson (entropy-maximizing family)
TipsDemographic projection pipelineParameter-free spatial interaction modelModel of flows between spatial origins and destinations
PirmavotsPreston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 978-1-557-86451-2Simini, F., González, M. C., Maritan, A., & Barabási, A.-L. (2012). A universal model for mobility and migration patterns. Nature, 484, 96–100. DOI ↗Wilson, 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 ProjeksiyonuRadiation Law of Human Mobility, Parameter-free Mobility Model, Simini Radiation Model, Radyasyon Modeligravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeli
Saistītās334
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.The Radiation Model, introduced by Simini et al. in 2012, is a parameter-free model for predicting human mobility and migration flows between geographic locations. Drawing an analogy from radiation physics, it predicts trip volumes based solely on population sizes at origin and destination, and the intervening population within the circle connecting them. It has been widely applied to commuting flows, migration, and epidemic spreading.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 · Radiation Model · Spatial Interaction Model. Izgūts 2026-06-18 no https://scholargate.app/lv/compare