Tool Principal Component Analysis
Principal Component Analysis (PCA) for tables.
References
- StatLib Web Site
- C-code by F.Murtagh
- Bahrenberg, G., Giese, E., Nipper, J. (1992): Statistische Methoden in der Geographie 2 - Multivariate Statistik. pp.198-277.
- Author: O.Conrad (c) 2010
- Menu: Table|Calculus
Parameters
| Name | Type | Identifier | Description | Constraints | |
|---|---|---|---|---|---|
| Input | Table | Table, input | TABLE | - | - |
| Output | Principal Components (*) | Table, output, optional | 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, output, optional -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