SAGA 9.4.2 | Tool Library Documentation

Multiple Regression Analysis (Points and Predictor Grids)


Description

Linear regression analysis of point attributes with multiple grids. Details of the regression/correlation analysis will be saved to a table. The regression function is used to create a new grid with regression based values. The multiple regression analysis uses a forward selection procedure.


References


Parameters

 NameTypeIdentifierDescriptionConstraints
InputPredictorsgrid list, inputPREDICTORS--
Pointsshapes, inputPOINTS--
OutputDetails: Coefficientstable, output, optionalINFO_COEFF--
Details: Modeltable, output, optionalINFO_MODEL--
Details: Stepstable, output, optionalINFO_STEPS--
Residualsshapes, output, optionalRESIDUALS--
Regressiongrid, outputREGRESSIONregression model applied to predictor grids-
Regression with Residual Correctiongrid, output, optionalREGRESCORRregression model applied to predictor grids with interpolated residuals added-
OptionsGrid Systemgrid systemPARAMETERS_GRID_SYSTEM--
Dependent Variabletable fieldATTRIBUTE--
ResamplingchoiceRESAMPLING-Available Choices: [0] Nearest Neighbour [1] Bilinear Interpolation [2] Bicubic Spline Interpolation [3] B-Spline Interpolation Default: 3
Include X CoordinatebooleanCOORD_X-Default: 0
Include Y CoordinatebooleanCOORD_Y-Default: 0
InterceptbooleanINTERCEPT-Default: 1
MethodchoiceMETHOD-Available Choices: [0] include all [1] forward [2] backward [3] stepwise Default: 3
Significance Levelfloating point numberP_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 Subsamplesinteger numberCROSSVAL_Knumber of subsamples for k-fold cross validationMinimum: 2 Default: 10
Residual InterpolationchoiceRESIDUAL_COR-Available Choices: [0] Multilevel B-Spline Interpolation [1] Inverse Distance Weighted Default: 0

Command Line


Usage: saga_cmd statistics_regression 1 [-PREDICTORS ] [-POINTS ] [-ATTRIBUTE ] [-INFO_COEFF ] [-INFO_MODEL ] [-INFO_STEPS ] [-RESIDUALS ] [-REGRESSION ] [-REGRESCORR ] [-RESAMPLING ] [-COORD_X ] [-COORD_Y ] [-INTERCEPT ] [-METHOD ] [-P_VALUE ] [-CROSSVAL ] [-CROSSVAL_K ] [-RESIDUAL_COR ]
  -PREDICTORS:  	Predictors
	grid list, input
  -POINTS:      	Points
	shapes, input
  -ATTRIBUTE:   	Dependent Variable
	table field
  -INFO_COEFF:  	Details: Coefficients
	table, output, optional
  -INFO_MODEL:  	Details: Model
	table, output, optional
  -INFO_STEPS:  	Details: Steps
	table, output, optional
  -RESIDUALS:   	Residuals
	shapes, output, optional
  -REGRESSION:  	Regression
	grid, output
  -REGRESCORR:  	Regression with Residual Correction
	grid, output, optional
  -RESAMPLING:  	Resampling
	choice
	Available Choices:
	[0] Nearest Neighbour
	[1] Bilinear Interpolation
	[2] Bicubic Spline Interpolation
	[3] B-Spline Interpolation
	Default: 3
  -COORD_X:     	Include X Coordinate
	boolean
	Default: 0
  -COORD_Y:     	Include Y Coordinate
	boolean
	Default: 0
  -INTERCEPT:   	Intercept
	boolean
	Default: 1
  -METHOD:      	Method
	choice
	Available Choices:
	[0] include all
	[1] forward
	[2] backward
	[3] stepwise
	Default: 3
  -P_VALUE:  	Significance Level
	floating point number
	Minimum: 0.000000
	Maximum: 100.000000
	Default: 5.000000
  -CROSSVAL:    	Cross Validation
	choice
	Available Choices:
	[0] none
	[1] leave one out
	[2] 2-fold
	[3] k-fold
	Default: 0
  -CROSSVAL_K:  	Cross Validation Subsamples
	integer number
	Minimum: 2
	Default: 10
  -RESIDUAL_COR:	Residual Interpolation
	choice
	Available Choices:
	[0] Multilevel B-Spline Interpolation
	[1] Inverse Distance Weighted
	Default: 0