Module Regression Analysis (Points and Predictor Grid)
Regression analysis of point attributes with a grid as predictor. The regression function is used to create a new grid with regression based values.
Reference:
- Bahrenberg, G., Giese, E., Nipper, J. (1990): 'Statistische Methoden in der Geographie 1 - Univariate und bivariate Statistik', Stuttgart, 233p.
- Author: O.Conrad (c) 2004
- Menu: Spatial and Geostatistics|Regression
Parameters
| | Name | Type | Identifier | Description | Constraints |
|---|
| Input | Predictor | Grid (input) | PREDICTOR | - | - |
| Points | Shapes (input) | POINTS | - | - |
| Output | Regression | Grid (output) | REGRESSION | - | - |
| Residuals (*) | Shapes (optional output) | RESIDUAL | - | - |
| Options | Grid system | Grid system | PARAMETERS_GRID_SYSTEM | Grid system | - |
| Dependent Variable | Table field | ATTRIBUTE | - | - |
| Resampling | Choice | RESAMPLING | - | Available Choices:
[0] Nearest Neighbour
[1] Bilinear Interpolation
[2] Bicubic Spline Interpolation
[3] B-Spline Interpolation
Default: 3 |
| Regression Function | Choice | METHOD | - | Available Choices:
[0] Y = a + b * X (linear)
[1] Y = a + b / X
[2] Y = a / (b - X)
[3] Y = a * X^b (power)
[4] Y = a e^(b * X) (exponential)
[5] Y = a + b * ln(X) (logarithmic)
Default: 0 |
| (*) optional |
Command-line
Usage: saga_cmd statistics_regression 0 [-PREDICTOR <str>] [-POINTS <str>] [-ATTRIBUTE <str>] [-REGRESSION <str>] [-RESIDUAL <str>] [-RESAMPLING <str>] [-METHOD <str>]
-PREDICTOR:<str> Predictor
Grid (input)
-POINTS:<str> Points
Shapes (input)
-ATTRIBUTE:<str> Dependent Variable
Table field
-REGRESSION:<str> Regression
Grid (output)
-RESIDUAL:<str> Residuals
Shapes (optional output)
-RESAMPLING:<str> Resampling
Choice
Available Choices:
[0] Nearest Neighbour
[1] Bilinear Interpolation
[2] Bicubic Spline Interpolation
[3] B-Spline Interpolation
Default: 3
-METHOD:<str> Regression Function
Choice
Available Choices:
[0] Y = a + b * X (linear)
[1] Y = a + b / X
[2] Y = a / (b - X)
[3] Y = a * X^b (power)
[4] Y = a e^(b * X) (exponential)
[5] Y = a + b * ln(X) (logarithmic)
Default: 0