GWR for Multiple Predictors (Shapes)
| Author(s) | O.Conrad (c) 2010 |
| Library ID | statistics_regression |
| Tool ID | 7 |
| Version | 1.0 |
| Menu | Spatial and Geostatistics | Geographically Weighted Regression |
Description
Geographically Weighted Regression for multiple predictors. Regression details are stored in a copy of the input data set. If the input data set is not a point data set, the feature centroids are used as spatial reference.
References
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
Parameters
| | Name | Type | Identifier | Description | Constraints |
|---|
| Input | Shapes | shapes, input | POINTS | - | - |
| Output | Regression | shapes, output | REGRESSION | - | - |
| Options | Dependent Variable | table field | DEPENDENT | - | - |
| Predictors | table fields | PREDICTORS | - | - |
| Logistic Regression | boolean | LOGISTIC | - | Default: 0 |
| 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: 1.000000 |
| Search Range | choice | SEARCH_RANGE | - | Available Choices:
[0] local
[1] global
Default: 1 |
| Maximum Search Distance | floating point number | SEARCH_RADIUS | local maximum search distance given in map units | Minimum: 0.000000
Default: 1000.000000 |
| Number of Points | choice | SEARCH_POINTS_ALL | - | Available Choices:
[0] maximum number of nearest points
[1] all points within search distance
Default: 1 |
| Minimum | integer number | SEARCH_POINTS_MIN | minimum number of points to use | Minimum: 1
Default: 16 |
| Maximum | integer number | SEARCH_POINTS_MAX | maximum number of nearest points | Minimum: 1
Default: 20 |
Command Line
Usage: saga_cmd statistics_regression 7 [-POINTS ] [-DEPENDENT ] [-PREDICTORS ] [-REGRESSION ] [-LOGISTIC ] [-DW_WEIGHTING ] [-DW_IDW_POWER ] [-DW_BANDWIDTH ] [-SEARCH_RANGE ] [-SEARCH_RADIUS ] [-SEARCH_POINTS_ALL ] [-SEARCH_POINTS_MIN ] [-SEARCH_POINTS_MAX ]
-POINTS: Shapes
shapes, input
-DEPENDENT: Dependent Variable
table field
-PREDICTORS: Predictors
table fields
-REGRESSION: Regression
shapes, output
-LOGISTIC: Logistic Regression
boolean
Default: 0
-DW_WEIGHTING:
Weighting Function
choice
Available Choices:
[0] no distance weighting
[1] inverse distance to a power
[2] exponential
[3] gaussian
Default: 3
-DW_IDW_POWER: Power
floating point number
Minimum: 0.000000
Default: 2.000000
-DW_BANDWIDTH: Bandwidth
floating point number
Minimum: 0.000000
Default: 1.000000
-SEARCH_RANGE: Search Range
choice
Available Choices:
[0] local
[1] global
Default: 1
-SEARCH_RADIUS: Maximum Search Distance
floating point number
Minimum: 0.000000
Default: 1000.000000
-SEARCH_POINTS_ALL:
Number of Points
choice
Available Choices:
[0] maximum number of nearest points
[1] all points within search distance
Default: 1
-SEARCH_POINTS_MIN: Minimum
integer number
Minimum: 1
Default: 16
-SEARCH_POINTS_MAX: Maximum
integer number
Minimum: 1
Default: 20