השוואת שיטות

	תחזית אוכלוסייה בשיטת קוהורט-רכיב	מודל הקרינה של ניידות והגירה	מודלים של אינטראקציה מרחבית (כבידה)
תחום	דמוגרפיה	ניתוח מרחבי	ניתוח מרחבי
משפחה	Process / pipeline	Regression model	Regression model
שנת המקור	2001	2012	1971
הוגה השיטה	Preston, Heuveline & Guillot	Filippo Simini et al.	Alan Wilson (entropy-maximizing family)
סוג	Demographic projection pipeline	Parameter-free spatial interaction model	Model of flows between spatial origins and destinations
מקור מכונן	Preston, S. H., Heuveline, P., & Guillot, M. (2001). Demography: Measuring and Modeling Population Processes. Blackwell. ISBN: 978-1-557-86451-2	Simini, F., González, M. C., Maritan, A., & Barabási, A.-L. (2012). A universal model for mobility and migration patterns. Nature, 484, 96–100.	Wilson, A. G. (1971). A family of spatial interaction models, and associated developments. Environment and Planning A, 3(1), 1–32.
כינויים	Cohort-Component Method, Component Method of Population Projection, Age-Sex-Specific Population Projection, Kohort-Bileşen Projeksiyonu	Radiation Law of Human Mobility, Parameter-free Mobility Model, Simini Radiation Model, Radyasyon Modeli	gravity model, spatial interaction model, competing destinations model, mekânsal etkileşim modeli
קשורות	3	3	4
תקציר	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 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.