Altaxo. |
[Missing <summary> documentation for "N:Altaxo.Calc.Regression.Multivariate"]
Classes| Class | Description | |
|---|---|---|
 | CrossPredictedXResidualsEvaluator | |
| CrossPredictedYEvaluator | |
| CrossPRESSEvaluator | |
| CrossValidationGroupingStrategyExcludeGroupsOfSimilarMeasurements | This strategy groups together similar observations, i.e. observations that have exactly the same target values. |
| CrossValidationGroupingStrategyExcludeGroupsOfSimilarMeasurementsSerializationSurrogate0 | |
| CrossValidationGroupingStrategyExcludeHalfObservations | This strategy groups the observations into two groups. It try to part observations with the same target values equally into the one group and the other group. |
| CrossValidationGroupingStrategyExcludeHalfObservationsSerializationSurrogate0 | |
| CrossValidationGroupingStrategyExcludeSingleMeasurements | Stragegy that groups each observation in an own group. |
| CrossValidationGroupingStrategyExcludeSingleMeasurementsSerializationSurrogate0 | |
| CrossValidationGroupingStrategyNone | Represents the no-grouping strategy. Thus a call to Group(IROMatrixDouble) will result in a NotImplementedException. |
| CrossValidationGroupingStrategyNoneSerializationSurrogate0 | |
| CrossValidationResult | Stores the result(s) of cross validation. |
| CrossValidationResultEvaluator | |
| CrossValidationWorker | |
| DimensionReductionAndRegressionDataSource | Data source for an algorithm based on dimension reduction and then regression of the reduced dimensions (PLS1, PLS2, PCR). |
| DimensionReductionAndRegressionOptions | Process options for the multivariate analyses that feature a dimension reduction and regression. |
| DimensionReductionAndRegressionOptionsSerializationSurrogate0 | |
| DimensionReductionAndRegressionPredictionDataSource | 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. |
| DimensionReductionAndRegressionPredictionProcessData | Contains the data used in DimensionReductionAndRegressionPredictionDataSource to predict data using a prediction model, and some spectral data. |
| DimensionReductionAndRegressionPreprocessedXDataSource | 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. |
| DimensionReductionAndRegressionResult | |
| DimensionReductionAndRegressionResultSerializationSurrogate0 | |
| MultivariateCalibrationModel | |
| MultivariateContentMemento | This class is for remembering the content of the PLS calibration and where to found the original data. |
| MultivariateContentMementoCrossPRESSCalculationTypeXmlSerializationSurrogate1 | |
| MultivariateLinearFitParameters | |
| MultivariateLinearRegression | Summary description for MultivariateLinearRegression. |
| MultivariatePreprocessingModel | |
| MultivariateRegression | Contains method common for all multivariate regressions. |
| PCRCalibrationModel | |
| PCRRegression | PCRRegression contains static methods for doing principal component regression analysis and prediction of the data. |
| PCRWorksheetAnalysis | PCRWorksheetAnalysis performs a principal component analysis and subsequent regression and stores the results in a given table |
| PCRWorksheetAnalysisSerializationSurrogate0 | |
| PLS1CalibrationModel | |
| PLS1Regression | Summary description for PLS1Regression. |
| PLS1WorksheetAnalysis | PLS2WorksheetAnalysis performs a PLS1 analysis and stores the results in a given table |
| PLS1WorksheetAnalysisSerializationSurrogate0 | |
| PLS2CalibrationModel | |
| PLS2Regression | PLSRegression contains static methods for doing partial least squares regression analysis and prediction of the data. |
| PLS2WorksheetAnalysis | PLS2WorksheetAnalysis performs a PLS2 analysis and stores the results in a given table |
| PLS2WorksheetAnalysisSerializationSurrogate0 | |
| SpectralPreprocessingOptions | SpectralPreprocessingOptions holds the options applied to all spectra before processed by PLS or PCR. |
| WorksheetAnalysis | WorksheetMethods provides common utility methods for multivariate data analysis. |
| WorksheetAnalysisOriginalDataTableNotFoundException |
Structures| Structure | Description | |
|---|---|---|
 | MultivariateAnalysisOptions | Determines how to do a Partial Least Squares Analysis. |
Interfaces| Interface | Description | |
|---|---|---|
 | ICrossValidationGroupingStrategy | Provides a strategie for grouping the data (spectra etc.) according to their corresponding calibration values (concentration etc). |
| ICrossValidationResult | Stores the result(s) of cross validation. |
| IMultivariateCalibrationModel | IMultivariateCalibrationModel contains the basic data for a multivariate calibration model |
| IMultivariatePreprocessingModel | Contains the basic data that where obtained during preprocessing. |
| IPLS2CalibrationModel |
Delegates| Delegate | Description | |
|---|---|---|
 | MultivariateRegressionCrossValidationIterationFunction | Function used for cross validation iteration. During cross validation, the original spectral matrix is separated into a spectral group used for prediction and the remaining calibration spectra. Parameters here: group: Indices of measurement that are excluded from the analysis (but then used for prediction). XXRaw: remaining calibration spectra (unpreprocessed). YYRaw: corresponding remaining concentration data (unpreprocessed). XURaw: spectra used for prediction (unpreprocessed). YURaw: corresponding concentration data (unpreprocessed). |
Enumerations| Enumeration | Description | |
|---|---|---|
 | CrossPRESSCalculationType | Determines how to do the calculation of Cross Validated Predicted Error Sum of Squares. |
| SpectralPreprocessingMethod | Gives the list of basic processing methods |