This paper describes preliminary work analysing the stability of parameter coefficient estimates for Geographically-Weighted Regression (GWR). Based on a large dataset (35721 points) various random samplings of this data were performed and models built using GWR. An analysis of the coefficient values for the independent variables showed that these values could varying significantly both between runs and between sampling sizes. This suggests that the results from GWR must be carefully considered in terms of the form of data, assumed coefficient surface being modelled, and the confidence of the resulting parameter estimates.PublishedNon Peer ReviewedBayley, A. & R. Goodyear (2001) An Urban/Rural Profile, Statistics New Zealand, . Brund...
The technique of geographically weighted regression (GWR) is used to model spatial ‘drift’ in linea...
Spatial nonstationarity is a condition in which a simple ‘global” model cannot explain the relations...
its variants are analysis methods that can cope with the multi-scale, spatially non-stationary relat...
This paper describes preliminary work analysing the stability of parameter coefficient estimates for...
This paper describes preliminary work analysing the stability of parameter coefficient estimates for...
This text is written as a follow-up to a two-day workshop on Geographically Weighted Regression (GWR...
This text is written as a follow-up to a two-day workshop on Geographically Weighted Regression (GWR...
Recent work on Geographically Weighted Regression (GWR) (Bruns- don, Fotheringham, and Charlton 199...
Recent work on Geographically Weighted Regression (GWR) (Bruns- don, Fotheringham, and Charlton 199...
Recent work on Geographically Weighted Regression (GWR) (Bruns- don, Fotheringham, and Charlton 199...
abstract: Geographically Weighted Regression (GWR) has been broadly used in various fields to model...
Recent work on Geographically Weighted Regression (GWR) (Bruns- don, Fotheringham, and Charlton 199...
The technique of geographically weighted regression (GWR) is used to model spatial ‘drift’ in linea...
Abstract Background Geographically weighted regression (GWR) is a modelling technique designed to de...
The technique of geographically weighted regression (GWR) is used to model spatial ‘drift’ in linea...
The technique of geographically weighted regression (GWR) is used to model spatial ‘drift’ in linea...
Spatial nonstationarity is a condition in which a simple ‘global” model cannot explain the relations...
its variants are analysis methods that can cope with the multi-scale, spatially non-stationary relat...
This paper describes preliminary work analysing the stability of parameter coefficient estimates for...
This paper describes preliminary work analysing the stability of parameter coefficient estimates for...
This text is written as a follow-up to a two-day workshop on Geographically Weighted Regression (GWR...
This text is written as a follow-up to a two-day workshop on Geographically Weighted Regression (GWR...
Recent work on Geographically Weighted Regression (GWR) (Bruns- don, Fotheringham, and Charlton 199...
Recent work on Geographically Weighted Regression (GWR) (Bruns- don, Fotheringham, and Charlton 199...
Recent work on Geographically Weighted Regression (GWR) (Bruns- don, Fotheringham, and Charlton 199...
abstract: Geographically Weighted Regression (GWR) has been broadly used in various fields to model...
Recent work on Geographically Weighted Regression (GWR) (Bruns- don, Fotheringham, and Charlton 199...
The technique of geographically weighted regression (GWR) is used to model spatial ‘drift’ in linea...
Abstract Background Geographically weighted regression (GWR) is a modelling technique designed to de...
The technique of geographically weighted regression (GWR) is used to model spatial ‘drift’ in linea...
The technique of geographically weighted regression (GWR) is used to model spatial ‘drift’ in linea...
Spatial nonstationarity is a condition in which a simple ‘global” model cannot explain the relations...
its variants are analysis methods that can cope with the multi-scale, spatially non-stationary relat...