SAGA-GIS Module Library Documentation (v2.2.3)

Module Multiple Linear Regression Analysis

Multiple linear regression analysis using ordinary least squares.

Parameters

 NameTypeIdentifierDescriptionConstraints
InputTableTable (input)TABLE--
OutputResults (*)Table (optional output)RESULTS--
Details: Coefficients (*)Table (optional output)INFO_COEFF--
Details: Model (*)Table (optional output)INFO_MODEL--
Details: Steps (*)Table (optional output)INFO_STEPS--
OptionsDependent VariableTable fieldDEPENDENT--
PredictorsParametersPREDICTORS-0 Parameters:
MethodChoiceMETHOD-Available Choices:
[0] include all
[1] forward
[2] backward
[3] stepwise
Default: 3
Significance LevelFloating pointP_VALUESignificance level (aka p-value) as threshold for automated predictor selection, given as percentageMinimum: 0.000000
Maximum: 100.000000
Default: 5.000000
Cross ValidationChoiceCROSSVAL-Available Choices:
[0] none
[1] leave one out
[2] 2-fold
[3] k-fold
Default: 0
Cross Validation SubsamplesIntegerCROSSVAL_Knumber of subsamples for k-fold cross validationMinimum: 2
Default: 10
(*) optional

Command-line

Usage: saga_cmd statistics_regression 12 [-TABLE <str>] [-RESULTS <str>] [-DEPENDENT <str>] [-INFO_COEFF <str>] [-INFO_MODEL <str>] [-INFO_STEPS <str>] [-METHOD <str>] [-P_VALUE <str>] [-CROSSVAL <str>] [-CROSSVAL_K <num>]
  -TABLE:<str>     	Table
	Table (input)
  -RESULTS:<str>   	Results
	Table (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:<str>   	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: 2
	Default: 10