PCRRegression (FsODE)

FsODE

Documentation for 0.0.2

PCRRegression Type

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

PCRRegression contains static methods for doing principal component regression analysis and prediction of the data.

Constructors

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

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.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
`PCRRegression.CalculatePRESS(yLoads, xScores, numberOfFactors, press)` Full Usage: `PCRRegression.CalculatePRESS(yLoads, xScores, numberOfFactors, press)` Parameters: yLoads : `IROMatrix<float>` xScores : `IROMatrix<float>` numberOfFactors : `int` press : `byref<IROVector<float>>`	yLoads : `IROMatrix<float>` xScores : `IROMatrix<float>` numberOfFactors : `int` press : `byref<IROVector<float>>`
`PCRRegression.CalculatePRESS(matrixX, xLoads, yLoads, xScores, crossProduct, numberOfFactors, PRESS)` Full Usage: `PCRRegression.CalculatePRESS(matrixX, xLoads, yLoads, xScores, crossProduct, numberOfFactors, PRESS)` Parameters: matrixX : `IROMatrix<float>` xLoads : `IROMatrix<float>` yLoads : `IROMatrix<float>` xScores : `IROMatrix<float>` crossProduct : `IReadOnlyList<float>` numberOfFactors : `int` PRESS : `byref<IROVector<float>>`	matrixX : `IROMatrix<float>` xLoads : `IROMatrix<float>` yLoads : `IROMatrix<float>` xScores : `IROMatrix<float>` crossProduct : `IReadOnlyList<float>` numberOfFactors : `int` PRESS : `byref<IROVector<float>>`
`PCRRegression.CalculateXLeverageFromPreprocessed(xScores, numberOfFactors, leverage)` Full Usage: `PCRRegression.CalculateXLeverageFromPreprocessed(xScores, numberOfFactors, leverage)` Parameters: xScores : `IROMatrix<float>` numberOfFactors : `int` leverage : `IMatrix<float>`	xScores : `IROMatrix<float>` numberOfFactors : `int` leverage : `IMatrix<float>`
`PCRRegression.CreateFromPreprocessed(matrixX, matrixY, maxFactors)` Full Usage: `PCRRegression.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: `PCRRegression` 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: `PCRRegression` A regression object, which holds all the loads and weights neccessary for further calculations.
`PCRRegression.ExecuteAnalysis(X, Y, numFactors, xLoads, xScores, V)` Full Usage: `PCRRegression.ExecuteAnalysis(X, Y, numFactors, xLoads, xScores, V)` Parameters: X : `IROMatrix<float>` Y : `IROMatrix<float>` numFactors : `byref<int>` xLoads : `byref<IROMatrix<float>>` xScores : `byref<IROMatrix<float>>` V : `byref<IROVector<float>>`	X : `IROMatrix<float>` Y : `IROMatrix<float>` numFactors : `byref<int>` xLoads : `byref<IROMatrix<float>>` xScores : `byref<IROMatrix<float>>` V : `byref<IROVector<float>>`
`PCRRegression.GetPredictionScoreMatrix(xLoads, yLoads, xScores, crossProduct, numberOfFactors, predictionScores)` Full Usage: `PCRRegression.GetPredictionScoreMatrix(xLoads, yLoads, xScores, crossProduct, numberOfFactors, predictionScores)` Parameters: xLoads : `IROMatrix<float>` yLoads : `IROMatrix<float>` xScores : `IROMatrix<float>` crossProduct : `IReadOnlyList<float>` numberOfFactors : `int` predictionScores : `IMatrix<float>`	xLoads : `IROMatrix<float>` yLoads : `IROMatrix<float>` xScores : `IROMatrix<float>` crossProduct : `IReadOnlyList<float>` numberOfFactors : `int` predictionScores : `IMatrix<float>`
`PCRRegression.GetSpectralResiduals(matrixX, xLoads, yLoads, xScores, crossProduct, numberOfFactors, spectralResiduals)` Full Usage: `PCRRegression.GetSpectralResiduals(matrixX, xLoads, yLoads, xScores, crossProduct, numberOfFactors, spectralResiduals)` Parameters: matrixX : `IROMatrix<float>` xLoads : `IROMatrix<float>` yLoads : `IROMatrix<float>` xScores : `IROMatrix<float>` crossProduct : `IReadOnlyList<float>` numberOfFactors : `int` spectralResiduals : `IMatrix<float>`	matrixX : `IROMatrix<float>` xLoads : `IROMatrix<float>` yLoads : `IROMatrix<float>` xScores : `IROMatrix<float>` crossProduct : `IReadOnlyList<float>` numberOfFactors : `int` spectralResiduals : `IMatrix<float>`
`PCRRegression.Predict(matrixX, xLoads, yLoads, xScores, crossProduct, numberOfFactors, predictedY, spectralResiduals)` Full Usage: `PCRRegression.Predict(matrixX, xLoads, yLoads, xScores, crossProduct, numberOfFactors, predictedY, spectralResiduals)` Parameters: matrixX : `IROMatrix<float>` xLoads : `IROMatrix<float>` yLoads : `IROMatrix<float>` xScores : `IROMatrix<float>` crossProduct : `IReadOnlyList<float>` numberOfFactors : `int` predictedY : `IMatrix<float>` spectralResiduals : `IMatrix<float>`	matrixX : `IROMatrix<float>` xLoads : `IROMatrix<float>` yLoads : `IROMatrix<float>` xScores : `IROMatrix<float>` crossProduct : `IReadOnlyList<float>` numberOfFactors : `int` predictedY : `IMatrix<float>` spectralResiduals : `IMatrix<float>`