Tool Multiple Linear Regression Analysis (Shapes)

Multiple linear regression analysis using ordinary least squares.

Author: O.Conrad (c) 2012
Menu: Spatial and Geostatistics|Regression|Shapes

Parameters

	Name	Type	Identifier	Description	Constraints
Input	Shapes	Shapes (input)	`TABLE`	-	-
Output	Results (*)	Shapes (optional output)	`RESULTS`	-	-
	Details: Coefficients (*)	Table (optional output)	`INFO_COEFF`	-	-
	Details: Model (*)	Table (optional output)	`INFO_MODEL`	-	-
	Details: Steps (*)	Table (optional output)	`INFO_STEPS`	-	-
Options	Dependent Variable	Table field	`DEPENDENT`	-	-
	Predictors	Parameters	`PREDICTORS`	-	0 Parameters:
	Method	Choice	`METHOD`	-	Available Choices: [0] include all [1] forward [2] backward [3] stepwise Default: 3
	Significance Level	Floating point	`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	`CROSSVAL_K`	number of subsamples for k-fold cross validation	Minimum: 0 Default: 10
(*) optional

Command-line

Usage: saga_cmd statistics_regression 13 [-TABLE <str>] [-RESULTS <str>] [-DEPENDENT <str>] [-INFO_COEFF <str>] [-INFO_MODEL <str>] [-INFO_STEPS <str>] [-METHOD <str>] [-P_VALUE <double>] [-CROSSVAL <str>] [-CROSSVAL_K <num>]
  -TABLE:<str>     	Shapes
	Shapes (input)
  -RESULTS:<str>   	Results
	Shapes (optional output)
  -DEPENDENT:<str> 	Dependent Variable
	Table field
  -INFO_COEFF:<str>	Details: Coefficients
	Table (optional output)
  -INFO_MODEL:<str>	Details: Model
	Table (optional output)
  -INFO_STEPS:<str>	Details: Steps
	Table (optional output)
  -METHOD:<str>    	Method
	Choice
	Available Choices:
	[0] include all
	[1] forward
	[2] backward
	[3] stepwise
	Default: 3
  -P_VALUE:<double>	Significance Level
	Floating point
	Minimum: 0.000000
	Maximum: 100.000000
	Default: 5.000000
  -CROSSVAL:<str>  	Cross Validation
	Choice
	Available Choices:
	[0] none
	[1] leave one out
	[2] 2-fold
	[3] k-fold
	Default: 0
  -CROSSVAL_K:<num>	Cross Validation Subsamples
	Integer
	Minimum: 0
	Default: 10