| Tool Name | GWR for Grid Downscaling |
| Tool ID | 14 |
| Library ID | statistics_regression |
| Version | 1.0 |
| Author(s) | O.Conrad (c) 2013 |
Fotheringham, S.A., Brunsdon, C., Charlton, M. (2002): Geographically Weighted Regression: the analysis of spatially varying relationships. John Wiley & Sons. online
Fotheringham, S.A., Charlton, M., Brunsdon, C. (1998): Geographically weighted regression: a natural evolution of the expansion method for spatial data analysis. Environment and Planning A 30(11), 1905–1927. online
Lloyd, C. (2010): Spatial Data Analysis - An Introduction for GIS Users. Oxford, 206p.
Zhang, D., Ren, N., and Hou, X. (2018): An improved logistic regression model based on a spatially weighted technique (ILRBSWT v1.0) and its application to mineral prospectivity mapping. Geosci. Model Dev., 11, 2525-2539. doi:10.5194/gmd-11-2525-2018
| Name | Type | Identifier | Description | Constraints |
|---|---|---|---|---|
| Input | ||||
| Predictors | grid list, input | PREDICTORS | ||
| Dependent Variable | grid, input | DEPENDENT | ||
| Output | ||||
| Regression | grid, output | REGRESSION | ||
| Regression with Residual Correction | grid, output, optional | REG_RESCORR | ||
| Coefficient of Determination | grid, output | QUALITY | ||
| Residuals | grid, output | RESIDUALS | ||
| Regression Parameters | grid list, output, optional | MODEL | ||
| Options | ||||
| Logistic Regression | boolean | LOGISTIC | Default: 0 | |
| Output of Model Parameters | boolean | MODEL_OUT | Default: 0 | |
| Search Range | choice | SEARCH_RANGE | Available Choices: [0] local [1] global Default: 0 | |
| Search Distance [Cells] | integer number | SEARCH_RADIUS | Minimum: 1 Default: 10 | |
| Weighting Function | choice | DW_WEIGHTING | Available Choices: [0] no distance weighting [1] inverse distance to a power [2] exponential [3] gaussian Default: 3 | |
| Power | floating point number | DW_IDW_POWER | Minimum: 0.000000 Default: 2.000000 | |
| Bandwidth | floating point number | DW_BANDWIDTH | Bandwidth for exponential and Gaussian weighting | Minimum: 0.000000 Default: 7.000000 |