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Priestorovo-časová sieťová priestorová analýza×Geograficky vážená regresia (GWR)×
OdborPriestorová analýzaPriestorová analýza
RodinaRegression modelRegression model
Rok vzniku1970–2000s2002
TvorcaTorsten Hägerstrand (time-geography foundation); extended by Harvey J. Miller and others for network contextsFotheringham, Brunsdon & Charlton
TypSpatiotemporal network modelLocal spatial regression
Pôvodný zdrojHägerstrand, T. (1970). What about people in regional science? Papers of the Regional Science Association, 24(1), 7–21. DOI ↗Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Ďalšie názvyST-NBA, space-time network analysis, spatiotemporal network analysis, network-based space-time analysisGWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Príbuzné25
ZhrnutieSpace-Time Network-Based Spatial Analysis integrates network topology with temporal constraints to model how people, goods, or phenomena move through geographic networks over time. Rooted in Hägerstrand's time-geography, it evaluates accessibility, interaction potential, and movement patterns along real-world infrastructure networks while respecting both spatial distance and time budgets.Geographically Weighted Regression is a local regression method, introduced by Fotheringham, Brunsdon and Charlton (2002), that allows the regression coefficients to vary across space. Instead of one global equation, it fits a separate set of coefficients at every location, capturing spatial heterogeneity in the relationships.
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ScholarGatePorovnať metódy: Space-Time Network-Based Spatial Analysis · Geographically Weighted Regression. Získané 2026-06-17 z https://scholargate.app/sk/compare