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