Tool Name	Multiple Regression Analysis (Grid and Predictor Grids)
Tool ID	8
Library ID	statistics_regression
Version	1.0
Author(s)	O.Conrad (c) 2011

Description

Linear regression analysis of one grid as dependent and multiple grids as independent (predictor) variables. Details of the regression/correlation analysis will be saved to a table. Optionally the regression model is used to create a new grid with regression based values. The multiple regression analysis uses a forward selection procedure.

References

Bahrenberg, G., Giese, E., Nipper, J. (1992): Statistische Methoden in der Geographie 2 - Multivariate Statistik. Stuttgart, 415p.

Parameters

Name	Type	Identifier	Description	Constraints
Input
Dependent Variable	grid, input	DEPENDENT
Predictors	grid list, input	PREDICTORS
Output
Regression	grid, output	REGRESSION
Residuals	grid, output, optional	RESIDUALS
Details: Coefficients	table, output, optional	INFO_COEFF
Details: Model	table, output, optional	INFO_MODEL
Details: Steps	table, output, optional	INFO_STEPS
Options
Resampling	choice	RESAMPLING		Available Choices: [0] Nearest Neighbour [1] Bilinear [2] Cubic 1 [3] Cubic 2 Default: 3
Include X Coordinate	boolean	COORD_X		Default: 0
Include Y Coordinate	boolean	COORD_Y		Default: 0
Method	choice	METHOD		Available Choices: [0] include all [1] forward [2] backward [3] stepwise Default: 3
Significance Level	floating point number	P_VALUE	Significance level (aka p-value) as threshold for automated predictor selection, given as percentage	Minimum: 0.000000 Maximum: 100.000000 Default: 5.000000
Cross Validation	choice	CROSSVAL		Available Choices: [0] none [1] leave one out [2] 2-fold [3] k-fold Default: 0
Cross Validation Subsamples	integer number	CROSSVAL_K	number of subsamples for k-fold cross validation	Minimum: 2 Default: 10