Pcrengine: Difference between revisions
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===Purpose=== | ===Purpose=== | ||
Principal components regression computational engine. | Principal components regression computational engine. | ||
===Synopsis=== | ===Synopsis=== | ||
:[reg,ssq,loads,scores,pcassq] = pcrengine(x,y,''ncomp,options'') | :[reg,ssq,loads,scores,pcassq] = pcrengine(x,y,''ncomp,options'') | ||
===Description=== | ===Description=== | ||
PCRENGINE calculates the basic elements of a PCR model (see PCR). | PCRENGINE calculates the basic elements of a PCR model (see PCR). | ||
Inputs are x the predictor x-block, and y the predicted y-block. | Inputs are x the predictor x-block, and y the predicted y-block. | ||
Optional input ''ncomp'' is the number of components to to be calculated (positive integer scalar). If the number of components ''ncomp'' is not specified, the routine will return components up to the rank of the x-block. Optional input ''options''. is discussed below. | Optional input ''ncomp'' is the number of components to to be calculated (positive integer scalar). If the number of components ''ncomp'' is not specified, the routine will return components up to the rank of the x-block. Optional input ''options''. is discussed below. | ||
Outputs are the matrix of regression vectors reg, the sum of squares captured ssq, x-block loadings loads, x-block scores scores, and the PCA ssqtable (pcassq). | Outputs are the matrix of regression vectors reg, the sum of squares captured ssq, x-block loadings loads, x-block scores scores, and the PCA ssqtable (pcassq). | ||
Note: The regression matrices are ordered in b such that each ''Ny'' (number of y-block variables) rows correspond to the regression matrix for that particular number of principal components. | Note: The regression matrices are ordered in b such that each ''Ny'' (number of y-block variables) rows correspond to the regression matrix for that particular number of principal components. | ||
===Options=== | ===Options=== | ||
* '''''options''''' = a structure array with the following fields: | * '''''options''''' = a structure array with the following fields: | ||
* '''display''': [ 'off' | {'on'} ], governs level of display to command window, | * '''display''': [ 'off' | {'on'} ], governs level of display to command window, | ||
* '''sortorder''': [ {'x'} | 'y' ], governs order of factors in outputs. 'x' is standard PCR sort order (ordered in terms of X block variance captured). 'y' is Correlation PCR sort order (ordered in terms of Y block variance captured). | * '''sortorder''': [ {'x'} | 'y' ], governs order of factors in outputs. 'x' is standard PCR sort order (ordered in terms of X block variance captured). 'y' is Correlation PCR sort order (ordered in terms of Y block variance captured). | ||
The default options can be retreived using: options = pcrengine('options');. | The default options can be retreived using: options = pcrengine('options');. | ||
===See Also=== | ===See Also=== | ||
[[analysis]], [[pcr]], [[pls]] | [[analysis]], [[pcr]], [[pls]] | ||
Revision as of 14:26, 3 September 2008
Purpose
Principal components regression computational engine.
Synopsis
- [reg,ssq,loads,scores,pcassq] = pcrengine(x,y,ncomp,options)
Description
PCRENGINE calculates the basic elements of a PCR model (see PCR).
Inputs are x the predictor x-block, and y the predicted y-block.
Optional input ncomp is the number of components to to be calculated (positive integer scalar). If the number of components ncomp is not specified, the routine will return components up to the rank of the x-block. Optional input options. is discussed below.
Outputs are the matrix of regression vectors reg, the sum of squares captured ssq, x-block loadings loads, x-block scores scores, and the PCA ssqtable (pcassq).
Note: The regression matrices are ordered in b such that each Ny (number of y-block variables) rows correspond to the regression matrix for that particular number of principal components.
Options
- options = a structure array with the following fields:
- display: [ 'off' | {'on'} ], governs level of display to command window,
- sortorder: [ {'x'} | 'y' ], governs order of factors in outputs. 'x' is standard PCR sort order (ordered in terms of X block variance captured). 'y' is Correlation PCR sort order (ordered in terms of Y block variance captured).
The default options can be retreived using: options = pcrengine('options');.