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
- Author: O.Conrad (c) 2010
- Menu: Spatial and Geostatistics|Grids|Principal Components
Parameters
| Name | Type | Identifier | Description | Constraints |
Input | Grids | Grid list, input | GRIDS | - | - |
Eigen Vectors (*) | Table, input, optional | EIGEN_INPUT | Use Eigen vectors from this table instead of calculating these from the input grids. | - |
Output | Principal Components | Grid list, output | PCA | - | - |
Eigen Vectors (*) | Table, output, optional | 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, input, optional
-EIGEN:<str> Eigen Vectors
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
-COMPONENTS:<num> Number of Components
Integer
Minimum: 0
Default: 3
-OVERWRITE:<str> Overwrite Previous Results
Boolean
Default: 1