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
- Specification: grid
- 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 | Dependent Variable | Table field | ATTRIBUTE | - | - |
| Grid Interpolation | Choice | INTERPOL | - | Available Choices: [0] Nearest Neighbor [1] Bilinear Interpolation [2] Inverse Distance Interpolation [3] Bicubic Spline Interpolation [4] B-Spline Interpolation Default: 4 | |
| 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>] [-INTERPOL <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) -INTERPOL:<str> Grid Interpolation Choice Available Choices: [0] Nearest Neighbor [1] Bilinear Interpolation [2] Inverse Distance Interpolation [3] Bicubic Spline Interpolation [4] B-Spline Interpolation Default: 4 -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