Multivariate |
public abstract class MultivariateRegression
The MultivariateRegression type exposes the following members.
Name | Description | |
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MultivariateRegression | Initializes a new instance of the MultivariateRegression class |
Name | Description | |
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CalibrationModel | Returns the calibration model of the analysis. | |
InternalCalibrationModel | Returns the calibration model of the analysis. | |
NumberOfFactors | Returns the number of factors calculated during the analysis. | |
NumberOfSpectralResiduals | This returns the number of spectral residuals. This is normally 1, but for the PLS1 analyis, it is the NumberOfY. |
Name | Description | |
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AnalyzeFromPreprocessed | Creates an analyis from preprocessed spectra and preprocessed concentrations. | |
AnalyzeFromPreprocessedWithoutReset | Creates an analyis from preprocessed spectra and preprocessed concentrations. | |
CrossValidationIteration | This function separates the spectra into a bunch of spectra used for calibration and the rest of spectra used for prediction. This separation is repeated until all spectra are used exactly one time for prediction. | |
Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) | |
Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object) | |
GetCrossPRESS | Get the cross predicted error sum of squares for the number of factors=0...numFactors. | |
GetCrossXResiduals | Calculates the spectral residuals obtained from cross validation. | |
GetCrossYPredicted | Calculates the cross predicted y values. | |
GetHashCode | Serves as the default hash function. (Inherited from Object) | |
GetPredictionScores | Calculates the prediction scores. | |
GetPRESSFromPreprocessed | Returns the predicted error sum of squares (PRESS) for this analysis. The length of the vector returned is the number of factors in the analysis plus one. | |
GetType | Gets the Type of the current instance. (Inherited from Object) | |
GetXLeverageFromPreprocessed | Calculates the spectral leverage from preprocessed spectra. | |
GetXLeverageFromRaw | Calculates the spectral leverage from raw spectra. | |
InternalGetPredictionScores | Calculates the prediction scores (for use with the preprocessed spectra). | |
InternalGetXLeverageFromPreprocessed | Calculates the spectral leverage values from the preprocessed spectra. | |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) | |
PostprocessTargetVariablesInline(IMultivariatePreprocessingModel, IMatrixDouble) | This calculates from the predicted (but still centered) y values the raw y values. | |
PostprocessTargetVariablesInline(IMatrixDouble, IReadOnlyListDouble, IReadOnlyListDouble) | This calculates from the predicted (but still centered) y values the raw y values. | |
PredictedYAndSpectralResidualsFromPreprocessed | This calculates the spectral residuals. | |
PredictYFromPreprocessed | This predicts concentrations of unknown spectra. | |
PredictYFromRaw | Predicts y values from raw (unpreprocessed) spectra. | |
PreprocessForAnalysis | Preprocesses the x and y matrices before usage in multivariate calibrations. | |
PreprocessSpectraForAnalysis | Preprocesses the spectra. This is the common first part, without ensemble processing. | |
PreprocessSpectraForPrediction(IMultivariateCalibrationModel, Double, IROMatrixDouble, Double, IMatrixDouble) | This will convert the raw spectra (horizontally in matrixX) to preprocessed spectra according to the calibration model. | |
PreprocessSpectraForPrediction(ISingleSpectrumPreprocessor, IEnsembleMeanScalePreprocessor, Double, IROMatrixDouble, IReadOnlyListDouble, IReadOnlyListDouble, Double, IMatrixDouble) | Preprocesses the x and y matrices before usage in multivariate calibrations. | |
PreprocessTargetVariablesForAnalysis | Preprocesses the x and y matrices before usage in multivariate calibrations. | |
PreprocessTargetVariablesForAnalysisInline | Preprocess the y values for analysis (mean center, scale currently not used). | |
Reset | Resets the regression, so that it appears like newly created. | |
SetCalibrationModel | This sets the calibration model data of the analysis to the provided data. This can be used to set back previously stored calibration data for use in the prediction functions. | |
SpectralResidualsFromPreprocessed(IROMatrixDouble, Int32) | This calculates the spectral residuals. | |
SpectralResidualsFromPreprocessed(IROMatrixDouble, Int32, IMatrixDouble) | This calculates the spectral residuals. | |
ToString | Returns a string that represents the current object. (Inherited from Object) |
Explanation of variables common to all methods:
NumberOfPoints: Number of measurements for calibration. Each measurement is represented by a spectrum X (or set of independent variables) and a set of corresponding concentrations Y (or dependent variables)
NumberOfX: Number of spectral values (or number of independent variables).
NumberOfY: Number of concentrations (or number of dependent variables).
NumberOfFactors: Number of main components used for prediction or calculation.
X: Matrix of spectra( or independent variables). The spectra are horizontal oriented, i.e. one spectra is a row in the X matrix.
Y: Matrix of concentration (or dependent variables). One set of concentrations is also represented by one row in the matrix.
XU: Matrix of unknown spectra (or independent variables) used for prediction of the Y variables.
SpectralRegions: If the spectra consists of more than one regions, these regions should be preprocessed separately. To designate them, one has to provide an array of ascending integer values. Each element of this region designates the starting index of a spectral region.