PLS1Regression (FsODE)

FsODE

Documentation for 0.0.2

PLS1Regression Type

Namespace: Altaxo.Calc.Regression.Multivariate
Assembly: AltaxoCore.Redist.dll
Base Type: MultivariateRegression

Summary description for PLS1Regression.

Constructors

Constructor	Description
`PLS1Regression()` Full Usage: `PLS1Regression()`

Instance members

Instance member	Description
`this.GetPRESSFromPreprocessed` Full Usage: `this.GetPRESSFromPreprocessed` Parameters: matrixX : `IROMatrix<float>` Returns: `IROVector<float>` Modifiers: abstract	matrixX : `IROMatrix<float>` Returns: `IROVector<float>`
`this.InternalCalibrationModel` Full Usage: `this.InternalCalibrationModel` Returns: `MultivariateCalibrationModel` Modifiers: abstract	Returns: `MultivariateCalibrationModel`
`this.NumberOfSpectralResiduals` Full Usage: `this.NumberOfSpectralResiduals` Returns: `int` Modifiers: abstract	Returns: `int`
`this.PRESS` Full Usage: `this.PRESS` Returns: `IROVector<float>`	Returns: `IROVector<float>`
`this.PredictedYAndSpectralResidualsFromPreprocessed` Full Usage: `this.PredictedYAndSpectralResidualsFromPreprocessed` Parameters: XU : `IROMatrix<float>` - Matrix of unknown spectra (preprocessed the same way as the calibration spectra). numFactors : `int` - Number of factors used for prediction. predictedY : `IMatrix<float>` - On return, holds the predicted y values. (They are centered). spectralResiduals : `IMatrix<float>` - On return, holds the spectral residual values. Modifiers: abstract	This predicts concentrations of unknown spectra. XU : `IROMatrix<float>` Matrix of unknown spectra (preprocessed the same way as the calibration spectra). numFactors : `int` Number of factors used for prediction. predictedY : `IMatrix<float>` On return, holds the predicted y values. (They are centered). spectralResiduals : `IMatrix<float>` On return, holds the spectral residual values.
`this.Reset` Full Usage: `this.Reset` Modifiers: abstract
`this.SetCalibrationModel` Full Usage: `this.SetCalibrationModel` Parameters: calib : `IMultivariateCalibrationModel` Modifiers: abstract	calib : `IMultivariateCalibrationModel`

Static members

Static member Description

Static member	Description
`PLS1Regression.CreateFromPreprocessed(matrixX, matrixY, maxFactors)` Full Usage: `PLS1Regression.CreateFromPreprocessed(matrixX, matrixY, maxFactors)` Parameters: matrixX : `IROMatrix<float>` - The spectral matrix (each spectrum is a row in the matrix). They must at least be centered. matrixY : `IROMatrix<float>` - The matrix of concentrations (each experiment is a row in the matrix). They must at least be centered. maxFactors : `int` - Maximum number of factors for analysis. Returns: `PLS1Regression` A regression object, which holds all the loads and weights neccessary for further calculations.	Creates an analyis from preprocessed spectra and preprocessed concentrations. matrixX : `IROMatrix<float>` The spectral matrix (each spectrum is a row in the matrix). They must at least be centered. matrixY : `IROMatrix<float>` The matrix of concentrations (each experiment is a row in the matrix). They must at least be centered. maxFactors : `int` Maximum number of factors for analysis. Returns: `PLS1Regression` A regression object, which holds all the loads and weights neccessary for further calculations.


                
                  
                    
                      PLS1Regression.CreateFromPreprocessed(matrixX, matrixY, maxFactors)

Full Usage: PLS1Regression.CreateFromPreprocessed(matrixX, matrixY, maxFactors)

Parameters:

matrixX : IROMatrix<float> - The spectral matrix (each spectrum is a row in the matrix). They must at least be centered.

matrixY : IROMatrix<float> - The matrix of concentrations (each experiment is a row in the matrix). They must at least be centered.

maxFactors : int - Maximum number of factors for analysis.

Returns: PLS1Regression A regression object, which holds all the loads and weights neccessary for further calculations.

Creates an analyis from preprocessed spectra and preprocessed concentrations.

matrixX : IROMatrix<float>: The spectral matrix (each spectrum is a row in the matrix). They must at least be centered.
matrixY : IROMatrix<float>: The matrix of concentrations (each experiment is a row in the matrix). They must at least be centered.
maxFactors : int: Maximum number of factors for analysis.

Returns: PLS1Regression: A regression object, which holds all the loads and weights neccessary for further calculations.