Сравнение методов

	Локальная пространственная регрессия	Регрессия с географически взвешенными коэффициентами (GWR)
Область	Пространственный анализ	Пространственный анализ
Семейство	Regression model	Regression model
Год появления	1996	2002
Автор метода	Brunsdon, Fotheringham & Charlton	Fotheringham, Brunsdon & Charlton
Тип	Spatially varying coefficient regression	Local spatial regression
Основополагающий источник	Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168	Fotheringham, A. S., Brunsdon, C., & Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley. ISBN: 978-0471496168
Другие названия	locally weighted spatial regression, spatially varying coefficient model, local spatial model, place-based regression	GWR, local regression, spatially varying coefficient regression, Coğrafi Ağırlıklı Regresyon (GWR)
Связанные	6	5
Сводка	Local Spatial Regression fits a separate regression model at each location in a study area, allowing regression coefficients to vary continuously across space. Rather than forcing one global slope on all observations, it reveals where and how the relationship between predictors and an outcome changes geographically — producing a map of coefficients rather than a single number.	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.