Tool Principal Component Analysis

Principal Component Analysis (PCA) for tables.

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: Table|Calculus

Parameters

	Name	Type	Identifier	Description	Constraints
Input	Table	Table (input)	`TABLE`	-	-
Output	Principal Components (*)	Table (optional output)	`PCA`	-	-
Options	Attributes	Parameters	`FIELDS`	-	0 Parameters:
	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	`NFIRST`	maximum number of calculated first components; set to zero to get all	Minimum: 0 Default: 3
(*) optional

Command-line

Usage: saga_cmd table_calculus 7 [-TABLE <str>] [-PCA <str>] [-METHOD <str>] [-NFIRST <num>]
  -TABLE:<str> 	Table
	Table (input)
  -PCA:<str>   	Principal Components
	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
  -NFIRST:<num>	Number of Components
	Integer
	Minimum: 0
	Default: 3