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Altaxo.Calc.Regression.Multivariate Namespace

[Missing <summary> documentation for "N:Altaxo.Calc.Regression.Multivariate"]

Classes
 ClassDescription
Public classCrossPredictedXResidualsEvaluator Evaluator that computes cross-validated residuals in X (spectral residuals).
Public classCrossPredictedYEvaluator Evaluates cross-validated predicted Y values.
Public classCrossPRESSEvaluator Evaluates the cross-validated predicted error sum of squares (Cross PRESS).
Public classCrossValidationGroupingStrategyExcludeGroupsOfSimilarMeasurements Groups together similar observations, i.e. observations that have exactly the same target values.
Public classCrossValidationGroupingStrategyExcludeGroupsOfSimilarMeasurementsSerializationSurrogate0 
Public classCrossValidationGroupingStrategyExcludeHalfObservations Groups the observations into two groups. It tries to split observations with the same target values as evenly as possible between the one group and the other group.
Public classCrossValidationGroupingStrategyExcludeHalfObservationsSerializationSurrogate0 
Public classCrossValidationGroupingStrategyExcludeSingleMeasurements Strategy that groups each observation into its own group.
Public classCrossValidationGroupingStrategyExcludeSingleMeasurementsSerializationSurrogate0 
Public classCrossValidationGroupingStrategyNone Represents the no-grouping strategy. Thus, a call to Group(IROMatrixDouble) will throw a NotImplementedException.
Public classCrossValidationGroupingStrategyNoneSerializationSurrogate0 
Public classCrossValidationResult Stores the result(s) of cross validation.
Public classCrossValidationResultEvaluator Evaluator that fills a CrossValidationResult instance with predicted Y values and spectral residuals for all factors.
Public classCrossValidationWorker Base class for cross validation evaluators. Provides common configuration and data required to perform cross validation for multivariate regression.
Public classDimensionReductionAndRegressionDataSource Data source for an algorithm based on dimension reduction and then regression of the reduced dimensions (PLS1, PLS2, PCR).
Public classDimensionReductionAndRegressionOptions Process options for the multivariate analyses that feature a dimension reduction and regression.
Public classDimensionReductionAndRegressionOptionsSerializationSurrogate0 
Public classDimensionReductionAndRegressionPredictionDataSource Data source of a table that contains predicted data. The data were predicted from a multivariate model (a table containing a DimensionReductionAndRegressionDataSource), and a table containing the spectra used for prediction.
Public classDimensionReductionAndRegressionPredictionProcessData Contains the data used in DimensionReductionAndRegressionPredictionDataSource to predict data using a prediction model, and some spectral data.
Public classDimensionReductionAndRegressionPreprocessedXDataSource Data source for a table that contains preprocessed spectra, originated from a DimensionReductionAndRegressionDataSource. Thus, this data source contains only a reference to a table containing the DimensionReductionAndRegressionDataSource. All data how to obtain the preprocessed spectra are contained in that data source.
Public classDimensionReductionAndRegressionResult
Public classDimensionReductionAndRegressionResultSerializationSurrogate0 
Public classMultivariateCalibrationModel Default implementation of IMultivariateCalibrationModel.
Public classMultivariateContentMemento This class is for remembering the content of the PLS calibration and where to found the original data.
Public classMultivariateContentMementoCrossPRESSCalculationTypeXmlSerializationSurrogate1 
Public classMultivariateLinearFitParameters 
Public classMultivariateLinearRegression Summary description for MultivariateLinearRegression.
Public classMultivariatePreprocessingModel Default implementation of IMultivariatePreprocessingModel.
Public classMultivariateRegression Contains methods common to all multivariate regressions.
Public classPCRCalibrationModel Calibration model for principal component regression (PCR).
Public classPCRRegression Implements principal component regression (PCR) analysis and prediction.
Public classPCRWorksheetAnalysis PCRWorksheetAnalysis performs a principal component analysis and subsequent regression and stores the results in a given table
Public classPCRWorksheetAnalysisSerializationSurrogate0 
Public classPLS1CalibrationModel Calibration model for PLS1 regression.
Public classPLS1Regression Implements Partial Least Squares regression (PLS1), i.e. PLS regression for multiple target variables by running a separate PLS2 model for each target variable.
Public classPLS1WorksheetAnalysis PLS2WorksheetAnalysis performs a PLS1 analysis and stores the results in a given table
Public classPLS1WorksheetAnalysisSerializationSurrogate0 
Public classPLS2CalibrationModel Calibration model for PLS2 regression.
Public classPLS2Regression Implements Partial Least Squares regression (PLS2) analysis and prediction.
Public classPLS2WorksheetAnalysis PLS2WorksheetAnalysis performs a PLS2 analysis and stores the results in a given table
Public classPLS2WorksheetAnalysisSerializationSurrogate0 
Public classSpectralPreprocessingOptions Holds options that are applied to all spectra before they are processed by PLS or PCR.
Public classWorksheetAnalysis WorksheetMethods provides common utility methods for multivariate data analysis.
Public classWorksheetAnalysisOriginalDataTableNotFoundException 
Structures
 StructureDescription
Public structureMultivariateAnalysisOptions Specifies options for running a multivariate analysis (e.g. Partial Least Squares).
Interfaces
 InterfaceDescription
Public interfaceICrossValidationGroupingStrategy Provides a strategy for grouping observation data (spectra, etc.) according to their corresponding calibration values (concentrations, etc.).
Public interfaceICrossValidationResult Stores the result(s) of cross validation.
Public interfaceIMultivariateCalibrationModel Contains the basic data for a multivariate calibration model.
Public interfaceIMultivariatePreprocessingModel Contains the basic data that were obtained during preprocessing.
Public interfaceIPLS2CalibrationModel Defines the calibration model data required by a PLS2 regression.
Delegates
 DelegateDescription
Public delegateMultivariateRegressionCrossValidationIterationFunction Function used for a cross-validation iteration. During cross validation, the original spectral matrix is separated into a spectral group used for prediction and the remaining calibration spectra.
Enumerations
 EnumerationDescription
Public enumerationCrossPRESSCalculationType Determines how to calculate the cross-validated predicted error sum of squares (Cross PRESS).
Public enumerationSpectralPreprocessingMethod Lists the available basic preprocessing methods.