SAGA 9.4.2 | Tool Library Documentation

Principal Component Analysis


Description

Principal Component Analysis (PCA) for grids. PCA implementation is based on F.Murtagh's code as provided by the StatLib web site.


References


Parameters

 NameTypeIdentifierDescriptionConstraints
InputGridsgrid list, inputGRIDS--
Eigen Vectorstable, input, optionalEIGEN_INPUTUse Eigen vectors from this table instead of calculating these from the input grids.-
OutputPrincipal Componentsgrid list, outputPCA--
Eigen Vectorstable, output, optionalEIGENStore calculated Eigen vectors to this table, e.g. for later use with forward or inverse PCA.-
OptionsGrid Systemgrid systemPARAMETERS_GRID_SYSTEM--
MethodchoiceMETHOD-Available Choices: [0] correlation matrix [1] variance-covariance matrix [2] sums-of-squares-and-cross-products matrix Default: 1
Number of Componentsinteger numberCOMPONENTSnumber of first components in the output; set to zero to get allMinimum: 0 Default: 3
Overwrite Previous ResultsbooleanOVERWRITE-Default: 1

Command Line


Usage: saga_cmd statistics_grid 8 [-GRIDS ] [-PCA ] [-EIGEN_INPUT ] [-EIGEN ] [-METHOD ] [-COMPONENTS ] [-OVERWRITE ]
  -GRIDS:      	Grids
	grid list, input
  -PCA:        	Principal Components
	grid list, output
  -EIGEN_INPUT:	Eigen Vectors
	table, input, optional
  -EIGEN:      	Eigen Vectors
	table, output, optional
  -METHOD:     	Method
	choice
	Available Choices:
	[0] correlation matrix
	[1] variance-covariance matrix
	[2] sums-of-squares-and-cross-products matrix
	Default: 1
  -COMPONENTS: 	Number of Components
	integer number
	Minimum: 0
	Default: 3
  -OVERWRITE:  	Overwrite Previous Results
	boolean
	Default: 1