Tool Principal Component Analysis

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

References

Bahrenberg, G., Giese, E., Nipper, J. (1992): Statistische Methoden in der Geographie 2 - Multivariate Statistik. pp.198-277.
C-code by F.Murtagh
StatLib Web Site

Author: O.Conrad (c) 2010
Menu: Spatial and Geostatistics|Grids|Principal Components

Parameters

	Name	Type	Identifier	Description	Constraints
Input	Grids	Grid list (input)	`GRIDS`	-	-
Input	Eigen Vectors (*)	Table (optional input)	`EIGEN_INPUT`	Use Eigen vectors from this table instead of calculating these from the input grids.	-
Output	Principal Components	Grid list (output)	`PCA`	-	-
Output	Eigen Vectors (*)	Table (optional output)	`EIGEN`	Store calculated Eigen vectors to this table, e.g. for later use with forward or inverse PCA.	-
Options	Grid system	Grid system	`PARAMETERS_GRID_SYSTEM`	-	-
	Method	Choice	`METHOD`	-	Available Choices: [0] correlation matrix [1] variance-covariance matrix [2] sums-of-squares-and-cross-products matrix Default: 1
	Number of Components	Integer	`COMPONENTS`	number of first components in the output; set to zero to get all	Minimum: 0 Default: 3
	Overwrite Previous Results	Boolean	`OVERWRITE`	-	Default: 1
(*) optional

Command-line

Usage: saga_cmd statistics_grid 8 [-GRIDS <str>] [-PCA <str>] [-EIGEN_INPUT <str>] [-EIGEN <str>] [-METHOD <str>] [-COMPONENTS <num>] [-OVERWRITE <str>]
  -GRIDS:<str>      	Grids
	Grid list (input)
  -PCA:<str>        	Principal Components
	Grid list (output)
  -EIGEN_INPUT:<str>	Eigen Vectors
	Table (optional input)
  -EIGEN:<str>      	Eigen Vectors
	Table (optional output)
  -METHOD:<str>     	Method
	Choice
	Available Choices:
	[0] correlation matrix
	[1] variance-covariance matrix
	[2] sums-of-squares-and-cross-products matrix
	Default: 1
  -COMPONENTS:<num> 	Number of Components
	Integer
	Minimum: 0
	Default: 3
  -OVERWRITE:<str>  	Overwrite Previous Results
	Boolean
	Default: 1