Functions
SQBatchEvolutionPrediction.h File Reference
#include "SQDef.h"
#include "SQErrorCodes.h"
#include "SQCommon.h"
#include "SQPrediction.h"
#include "SQIntVector.h"
#include "SQVectorData.h"

Go to the source code of this file.

Functions

SQ_ErrorCode SQ_GetAlignedContributionsDModXPS (SQ_Prediction pPrediction, float fMaturity, SQ_WeightType eWeightType, int iComponent, SQ_ReconstructState bReconstruct, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedContributionsDModXGroupPS (SQ_Prediction pPrediction, SQ_FloatVector *pMaturity, SQ_IntVector *pPhaseIteration, SQ_WeightType eWeightType, int iComponent, SQ_ReconstructState bReconstruct, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedContributionsDModYPS (SQ_Prediction pPrediction, float fMaturity, SQ_WeightType eWeightType, int iComponent, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedContributionsDModYGroupPS (SQ_Prediction pPrediction, SQ_FloatVector *pMaturity, SQ_IntVector *pPhaseIteration, SQ_WeightType eWeightType, int iComponent, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedContributionsScorePSSingleWeight (SQ_Prediction pPrediction, float fMaturity1, SQ_Bool bAverage, float fMaturity2, SQ_WeightType eWeightType, int iComponent, SQ_ReconstructState bReconstruct, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedContributionsScorePSSingleWeightGroup (SQ_Prediction pPrediction, SQ_FloatVector *pMaturity1, SQ_IntVector *pPhaseIteration1, SQ_Bool bAverage, SQ_FloatVector *pMaturity2, SQ_IntVector *pPhaseIteration2, SQ_WeightType eWeightType, int iComponent, SQ_ReconstructState bReconstruct, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedContributionsScorePSMultiWeight (SQ_Prediction pPrediction, float fMaturity1, SQ_Bool bAverage, float fMaturity2, SQ_IntVector *pWeightType, SQ_IntVector *pComponents, SQ_ReconstructState bReconstruct, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedContributionsScorePSMultiWeightGroup (SQ_Prediction pPrediction, SQ_FloatVector *pMaturity1, SQ_IntVector *pPhaseIteration1, SQ_Bool bAverage, SQ_FloatVector *pMaturity2, SQ_IntVector *pPhaseIteration2, SQ_IntVector *pWeightType, SQ_IntVector *pComponents, SQ_ReconstructState bReconstruct, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedDModXPS (SQ_Prediction pPrediction, int iComponent, SQ_NormalizedState bNormalized, SQ_ModelingPowerWeightedState bModelingPowerWeighted, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedTPS (SQ_Prediction pPrediction, int iComponent, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedToPS (SQ_Prediction pPrediction, int iComponent, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedT2RangePS (SQ_Prediction pPrediction, int iCompFrom, int iCompTo, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedTimeMaturityPS (SQ_Prediction pPrediction, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedXVarPS (SQ_Prediction pPrediction, SQ_UnscaledState bUnscaled, SQ_BacktransformedState bBackTransformed, int iXTerm, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedYPredPS (SQ_Prediction pPrediction, int iComponent, SQ_UnscaledState bUnscaled, SQ_BacktransformedState bBackTransformed, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedYVarPS (SQ_Prediction pPrediction, SQ_UnscaledState bUnscaled, SQ_BacktransformedState bBackTransformed, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedDModXPSOOCSum (SQ_Prediction pPrediction, int iComponent, float fLimit, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedTPSOOCSum (SQ_Prediction pPrediction, int iComponent, float fHighLimit, float fLowLimit, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedT2RangePSOOCSum (SQ_Prediction pPrediction, int iCompFrom, int iCompTo, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedXVarPSOOCSum (SQ_Prediction pPrediction, SQ_UnscaledState bUnscaled, SQ_BacktransformedState bBackTransformed, int iColumnXIndex, float fHighLimit, float fLowLimit, SQ_VectorData *pVectorData)
 
SQ_ErrorCode SQ_GetAlignedYPredPSOOCSum (SQ_Prediction pPrediction, int iComponent, SQ_UnscaledState bUnscaled, SQ_BacktransformedState bBackTransformed, float fHighLimit, float fLowLimit, SQ_VectorData *pVectorData)
 

Detailed Description

This file list the functions that are available for a prediction on a BEM.

Function Documentation

◆ SQ_GetAlignedContributionsDModXGroupPS()

SQ_ErrorCode SQ_GetAlignedContributionsDModXGroupPS ( SQ_Prediction  pPrediction,
SQ_FloatVector pMaturity,
SQ_IntVector pPhaseIteration,
SQ_WeightType  eWeightType,
int  iComponent,
SQ_ReconstructState  bReconstruct,
SQ_VectorData pVectorData 
)

Get the aligned DModX group contributions from the predicted results. Contribution is used to understand how an observation differs from the others in an X score(t) or in DModX. See the document "SIMCA-Q Interface Description.doc" for a more detailed description on contributions. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]pMaturityA vector with the maturity to get the contribution for.
[in]pPhaseIterationA vector of phase iteration names for which you would like to get contributions. If the project doesn't have a phase iteration ID the parameter is ignored.
[in]eWeightTypeThe type of weight. If the model is a PCA model this parameter must be Normalized, RX. If the model is a PLS model this parameter must be Normalized, RX, CoeffCS or VIP.
[in]iComponentThe component of the weight. Ignored if eWeightType=Normalized.
[in]bReconstructIf the project is a wavelet spectral compressed project and this parameter is true the returned matrix will be back transformed to the original domain.
[out]pVectorDataA pointer to the aligned DModXPS contribution results. Number of rows in matrix = 1. Number of columns in matrix = number of x-variables in the model.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedContributionsDModXPS()

SQ_ErrorCode SQ_GetAlignedContributionsDModXPS ( SQ_Prediction  pPrediction,
float  fMaturity,
SQ_WeightType  eWeightType,
int  iComponent,
SQ_ReconstructState  bReconstruct,
SQ_VectorData pVectorData 
)

Get the aligned DModX contributions from the predicted results. Contribution is used to understand how an observation differs from the others in an X score(t) or in DModX. See the document "SIMCA-Q Interface Description.doc" for a more detailed description on contributions. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]fMaturityThe maturity to get the contribution for.
[in]eWeightTypeThe type of weight. If the model is a PCA model this parameter must be Normalized, RX. If the model is a PLS model this parameter must be Normalized, RX, CoeffCS or VIP.
[in]iComponentThe component of the weight. Ignored if eWeightType=Normalized.
[in]bReconstructIf the project is a wavelet spectral compressed project and this parameter is true the returned matrix will be back transformed to the original domain.
[out]pVectorDataA pointer to the aligned DModXPS contribution results. Number of rows in matrix = 1. Number of columns in matrix = number of x-variables in the model.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedContributionsDModYGroupPS()

SQ_ErrorCode SQ_GetAlignedContributionsDModYGroupPS ( SQ_Prediction  pPrediction,
SQ_FloatVector pMaturity,
SQ_IntVector pPhaseIteration,
SQ_WeightType  eWeightType,
int  iComponent,
SQ_VectorData pVectorData 
)

Get the aligned DModY group contributions from the predicted results. Contribution is used to understand how an observation differs from the others in an X score(t) or in DModX. See the document "SIMCA-Q Interface Description.doc" for a more detailed description on contributions. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]pMaturityA vector with the maturity to get the contribution for.
[in]pPhaseIterationA vector of phase iteration names for which you would like to get contributions. If the project doesn't have a phase iteration ID the parameter is ignored. If iBatchIx <1 it is also ignored and can be NULL.
[in]eWeightTypeThe type of weight. Must be Normalized or RY.
[in]iComponentThe component of the weight.
[out]pVectorDataA pointer to the aligned DModYPS contribution results. Number of rows in matrix = 1. Number of columns in matrix = 1.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedContributionsDModYPS()

SQ_ErrorCode SQ_GetAlignedContributionsDModYPS ( SQ_Prediction  pPrediction,
float  fMaturity,
SQ_WeightType  eWeightType,
int  iComponent,
SQ_VectorData pVectorData 
)

Get the aligned DModY contributions from the predicted results. Contribution is used to understand how an observation differs from the others in an X score(t) or in DModX. See the document "SIMCA-Q Interface Description.doc" for a more detailed description on contributions. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]fMaturityThe maturity to get the contribution for.
[in]eWeightTypeThe type of weight. Must be Normalized or RY.
[in]iComponentThe component of the weight.
[out]pVectorDataA pointer to the aligned DModYPS contribution results. Number of rows in matrix = 1. Number of columns in matrix = number of x-variables in the model.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedContributionsScorePSMultiWeight()

SQ_ErrorCode SQ_GetAlignedContributionsScorePSMultiWeight ( SQ_Prediction  pPrediction,
float  fMaturity1,
SQ_Bool  bAverage,
float  fMaturity2,
SQ_IntVector pWeightType,
SQ_IntVector pComponents,
SQ_ReconstructState  bReconstruct,
SQ_VectorData pVectorData 
)

Get the aligned score multi weight contributions from the predicted results. Contribution is used to understand how an observation differs from the others in an X score(t) or in DModX. See the document "SIMCA-Q Interface Description.doc" for a more detailed description on contributions. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]fMaturity1The maturity of the reference observation (from observation).
[in]bAverageTrue if the reference maturity is average batch, false otherwise.
[in]fMaturity2The maturity for which the contributions are to be calculated (to observation).
[in]pWeightTypeAn int vector containing SQ_WeightType enums. If the model is a PCA model this parameter must be P. If the model is a PLS model this parameter must be P or WStar. If the model is a OPLS model this parameter must be P or PO.
[in]pComponentsA list of component Indices to use. 1 for component 1 in the model, 2 for component 2 and so on. NULL if all components in the model should be used. for OPLS models and PRange weight the component argument is ignored, all components are used, for weight Po the component argument is the orthogonal component number and the model must be OPLS for P_Po, supply 2 components, one predictive component and one orthogonal component.
[in]bReconstructIf the project is a wavelet spectral compressed project and this parameter is true the returned matrix will be back transformed to the original domain.
[out]pVectorDataA pointer to the aligned Score single weight contribution results. Number of rows in matrix = 1. Number of columns in matrix = number of x-variables in the model.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedContributionsScorePSMultiWeightGroup()

SQ_ErrorCode SQ_GetAlignedContributionsScorePSMultiWeightGroup ( SQ_Prediction  pPrediction,
SQ_FloatVector pMaturity1,
SQ_IntVector pPhaseIteration1,
SQ_Bool  bAverage,
SQ_FloatVector pMaturity2,
SQ_IntVector pPhaseIteration2,
SQ_IntVector pWeightType,
SQ_IntVector pComponents,
SQ_ReconstructState  bReconstruct,
SQ_VectorData pVectorData 
)

Get the aligned score multi weight group contributions from the predicted results. Contribution is used to understand how an observation differs from the others in an X score(t) or in DModX. See the document "SIMCA-Q Interface Description.doc" for a more detailed description on contributions. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]pMaturity1Vector with the maturity of the reference observations (from observations).
[in]pPhaseIteration1A vector of phase iteration names for which you would like to get contributions. If the project doesn't have a phase iteration ID the parameter is ignored. If iBatchIx <1 it is also ignored and can be NULL.
[in]bAverageTrue if the reference maturity is average batch, false otherwise.
[in]pMaturity2Vector with the maturity for which the contributions are to be calculated (to observations).
[in]pPhaseIteration2A vector of phase iteration names for which you would like to get contributions. If the project doesn't have a phase iteration ID the parameter is ignored. If iBatchIx <1 it is also ignored and can be NULL.
[in]pWeightTypeAn int vector containing SQ_WeightType enums. If the model is a PCA model this parameter must be P. If the model is a PLS model this parameter must be P or WStar. If the model is a OPLS model this parameter must be P or PO.
[in]pComponentsA list of component Indices to use. 1 for component 1 in the model, 2 for component 2 and so on. NULL if all components in the model should be used. for OPLS models and PRange weight the component argument is ignored, all components are used, for weight Po the component argument is the orthogonal component number and the model must be OPLS for P_Po, supply 2 components, one predictive component and one orthogonal component.
[in]bReconstructIf the project is a wavelet spectral compressed project and this parameter is true the returned matrix will be back transformed to the original domain.
[out]pVectorDataA pointer to the aligned Score single weight contribution results. Number of rows in matrix = 1. Number of columns in matrix = number of x-variables in the model.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedContributionsScorePSSingleWeight()

SQ_ErrorCode SQ_GetAlignedContributionsScorePSSingleWeight ( SQ_Prediction  pPrediction,
float  fMaturity1,
SQ_Bool  bAverage,
float  fMaturity2,
SQ_WeightType  eWeightType,
int  iComponent,
SQ_ReconstructState  bReconstruct,
SQ_VectorData pVectorData 
)

Get the aligned score single weight contributions from the predicted results. Contribution is used to understand how an observation differs from the others in an X score(t) or in DModX. See the document "SIMCA-Q Interface Description.doc" for a more detailed description on contributions. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]fMaturity1The maturity of the reference observation (from observation).
[in]bAverageTrue if the reference maturity is average batch, false otherwise.
[in]fMaturity2The maturity for which the contributions are to be calculated (to observation).
[in]eWeightTypeThe type of weight. If the model is a PCA model this parameter must be Normalized, Raw, RX or P. If the model is a PLS model this parameter can be any weight defined in SQX_WeightType.
[in]iComponentThe component of the weight. Ignored if eWeightType=Normalized or Raw.
[in]bReconstructIf the project is a wavelet spectral compressed project and this parameter is true the returned matrix will be back transformed to the original domain.
[out]pVectorDataA pointer to the aligned Score single weight contribution results. Number of rows in matrix = 1. Number of columns in matrix = number of x-variables in the model.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedContributionsScorePSSingleWeightGroup()

SQ_ErrorCode SQ_GetAlignedContributionsScorePSSingleWeightGroup ( SQ_Prediction  pPrediction,
SQ_FloatVector pMaturity1,
SQ_IntVector pPhaseIteration1,
SQ_Bool  bAverage,
SQ_FloatVector pMaturity2,
SQ_IntVector pPhaseIteration2,
SQ_WeightType  eWeightType,
int  iComponent,
SQ_ReconstructState  bReconstruct,
SQ_VectorData pVectorData 
)

Get the aligned score single weight group contributions from the predicted results. Contribution is used to understand how an observation differs from the others in an X score(t) or in DModX. See the document "SIMCA-Q Interface Description.doc" for a more detailed description on contributions. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]pMaturity1Vector with the maturity of the reference observations (from observations).
[in]pPhaseIteration1A vector of phase iteration names for which you would like to get contributions. If the project doesn't have a phase iteration ID the parameter is ignored. If iBatchIx <1 it is also ignored and can be NULL.
[in]bAverageTrue if the reference maturity is average batch, false otherwise.
[in]pMaturity2Vector with the maturity for which the contributions are to be calculated (to observations).
[in]pPhaseIteration2A vector of phase iteration names for which you would like to get contributions. If the project doesn't have a phase iteration ID the parameter is ignored. If iBatchIx <1 it is also ignored and can be NULL.
[in]eWeightTypeThe type of weight. If the model is a PCA model this parameter must be Normalized, Raw, RX or P. If the model is a PLS model this parameter can be any weight defined in SQX_WeightType.
[in]iComponentThe component of the weight. Ignored if eWeightType=Normalized or Raw.
[in]bReconstructIf the project is a wavelet spectral compressed project and this parameter is true the returned matrix will be back transformed to the original domain.
[out]pVectorDataA pointer to the aligned Score single weight contribution results. Number of rows in matrix = 1. Number of columns in matrix = number of x-variables in the model.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedDModXPS()

SQ_ErrorCode SQ_GetAlignedDModXPS ( SQ_Prediction  pPrediction,
int  iComponent,
SQ_NormalizedState  bNormalized,
SQ_ModelingPowerWeightedState  bModelingPowerWeighted,
SQ_VectorData pVectorData 
)

Retrieves the aligned DModX from the predicted data. Distance to the model in the X space (row residual SD), after xx components (the selected dimension), for new observations in the predictions. If you select component 0, it is the Stdev of the observations as scaled in the workset. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]iComponentThe number of the component in the model we want the results from
[in]bNormalizedIf SQ_True, the results will be in units of standard deviation of the pooled RSD of the model If SQ_False, they will be in absolute values.
[in]bModelingPowerWeightedIf SQ_True, the function will weight the residuals by the modeling power of the variables.
[out]pVectorDataA pointer to the aligned DModX results. Number of rows in matrix = 1. Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedDModXPSOOCSum()

SQ_ErrorCode SQ_GetAlignedDModXPSOOCSum ( SQ_Prediction  pPrediction,
int  iComponent,
float  fLimit,
SQ_VectorData pVectorData 
)

Out Of Control for DModXPS

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]iComponentThe component in the model to get the result from.
[in]fLimitThe sigma limit.
[out]pVectorDataA pointer to the aligned DModXPS OOC results. Number of rows in matrix = 1. Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedT2RangePS()

SQ_ErrorCode SQ_GetAlignedT2RangePS ( SQ_Prediction  pPrediction,
int  iCompFrom,
int  iCompTo,
SQ_VectorData pVectorData 
)

Retrieves the aligned T2Range from the predicted data. Hotelling T2RangePS is a combination of all the scores (tPS) in the selected range of components. It is a measure of how far away an observation is from the center of a PC or PLS model hyperplane in the selected range of components. The function fails if the model doesn't have any components. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]iCompFromThe first component in the requested range.
[in]iCompToThe last component in the requested range. Use -1 if you want it to be the last component in model. This is the preferred way for OPLS which always requires the last component.
[out]pVectorDataA pointer to the aligned T2Range results. Number of rows in matrix = 1. Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedT2RangePSOOCSum()

SQ_ErrorCode SQ_GetAlignedT2RangePSOOCSum ( SQ_Prediction  pPrediction,
int  iCompFrom,
int  iCompTo,
SQ_VectorData pVectorData 
)

Out Of Control for T2RangePS

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]iCompFromThe first component in the requested range.
[in]iCompToThe last component in the requested range. Use -1 if you want it to be the last component in model. This is the preferred way for OPLS which always requires the last component.
[out]pVectorDataA pointer to the aligned T2RangePS OOC results. Number of rows in matrix = 1. Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedTimeMaturityPS()

SQ_ErrorCode SQ_GetAlignedTimeMaturityPS ( SQ_Prediction  pPrediction,
SQ_VectorData pVectorData 
)

The Time or Maturity variable. Determining the end point of a Batch/phase from the predicted data. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[out]pVectorDataA pointer to the aligned Time/Maturity results. Number of rows in matrix = 1. Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedToPS()

SQ_ErrorCode SQ_GetAlignedToPS ( SQ_Prediction  pPrediction,
int  iComponent,
SQ_VectorData pVectorData 
)

Retrieves the aligned To from the predicted data. The predicted scores, (for new observations), one vector for each model dimension. They are new variables, computed from the model. They summarize X, to best approximate X (PC model), and both approximate X and predict Y (PLS model). The function fails if the model doesn't have any components. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]iComponentThe component to use.
[out]pVectorDataA pointer to the aligned To results. Number of rows in matrix = 1 (only one component) Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedTPS()

SQ_ErrorCode SQ_GetAlignedTPS ( SQ_Prediction  pPrediction,
int  iComponent,
SQ_VectorData pVectorData 
)

Retrieves the aligned T from the predicted data. The predicted scores, (for new observations), one vector for each model dimension. They are new variables, computed from the model. They summarize X, to best approximate X (PC model), and both approximate X and predict Y (PLS model). The function fails if the model doesn't have any components. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]iComponentThe component to use.
[out]pVectorDataA pointer to the aligned T results. Number of rows in matrix = 1 (only one component) Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedTPSOOCSum()

SQ_ErrorCode SQ_GetAlignedTPSOOCSum ( SQ_Prediction  pPrediction,
int  iComponent,
float  fHighLimit,
float  fLowLimit,
SQ_VectorData pVectorData 
)

Out Of Control for TPS

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]iComponentThe component in the model to get the result from.
[in]fHighLimitThe higher sigma limit.
[in]fLowLimitThe lower sigma limit.
[out]pVectorDataA pointer to the aligned TPS OOC results. Number of rows in matrix = 1. Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedXVarPS()

SQ_ErrorCode SQ_GetAlignedXVarPS ( SQ_Prediction  pPrediction,
SQ_UnscaledState  bUnscaled,
SQ_BacktransformedState  bBackTransformed,
int  iXTerm,
SQ_VectorData pVectorData 
)

Retrieves the predicted aligned XVar from a model. X variable from the predictions, in original units. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]bUnscaledIf SQ_TRUE, the function will return the x-values in the (unscaled) metric of the dataset. If SQ_FALSE, the returned x-values will be in the scaled and centered metric of the workset. Note that if bBackTransformed is SQ_FALSE, the x-values will still be transformed. Note also that if bBackTransformed is SQ_TRUE, this parameter is ignored. In this case x-values will always be unscaled.
[in]bBackTransformedIf SQ_TRUE, the function will return the x-values in the unscaled untransformed metric of the workset. If SQ_FALSE the returned x-values will be transformed in the same way as the workset. Note that if this variable is SQ_TRUE, the returned x-values will always be unscaled irrespective of the value of bUnscaled.
[in]iXTermThe X term to use.
[out]pVectorDataA pointer to the aligned XVar results. Number of rows in matrix = number of x-variables chosen. Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedXVarPSOOCSum()

SQ_ErrorCode SQ_GetAlignedXVarPSOOCSum ( SQ_Prediction  pPrediction,
SQ_UnscaledState  bUnscaled,
SQ_BacktransformedState  bBackTransformed,
int  iColumnXIndex,
float  fHighLimit,
float  fLowLimit,
SQ_VectorData pVectorData 
)

Out Of Control for XVarPS

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]bUnscaledIf SQ_TRUE, the function will return the x-values in the (unscaled) metric of the dataset. If SQ_FALSE, the returned x-values will be in the scaled and centered metric of the workset. Note that if bBackTransformed is SQ_FALSE, the x-values will still be transformed. Note also that if bBackTransformed is SQ_TRUE, this parameter is ignored. In this case x-values will always be unscaled.
[in]bBackTransformedIf SQ_TRUE, the function will return the x-values in the unscaled untransformed metric of the workset. If SQ_FALSE the returned x-values will be transformed in the same way as the workset. Note that if this variable is SQ_TRUE, the returned x-values will always be unscaled irrespective of the value of bUnscaled.
[in]iColumnXIndexThe index of the X-columns.
[in]fHighLimitThe higher sigma limit.
[in]fLowLimitThe lower sigma limit.
[out]pVectorDataA pointer to the aligned XVarPS OOC results. Number of rows in matrix = 1. Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedYPredPS()

SQ_ErrorCode SQ_GetAlignedYPredPS ( SQ_Prediction  pPrediction,
int  iComponent,
SQ_UnscaledState  bUnscaled,
SQ_BacktransformedState  bBackTransformed,
SQ_VectorData pVectorData 
)

Retrieves the aligned YPredPS. Aligned predicted values of the time/maturity variable in the predictions. The function fails if the model doesn't have any components. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]iComponentThe number of the component in the model we want the results from
[in]bUnscaledIf SQ_TRUE, the function will return the y-values in the (unscaled) metric of the dataset. If SQ_FALSE, the returned y-values will be in the scaled and centered metric of the workset. Note that if bBackTransformed is SQ_FALSE, the y-values will still be transformed. Note also that if bBackTransformed is SQ_TRUE, this parameter is ignored. In this case y-values will always be unscaled.
[in]bBackTransformedIf SQ_TRUE, the function will return the y-values in the unscaled untransformed metric of the workset. If SQ_FALSE the returned y-values will be transformed in the same way as the workset. Note that if this variable is SQ_TRUE, the returned y-values will always be unscaled irrespective of the value of bUnscaled.
[out]pVectorDataA pointer to the aligned YPredPS results. Number of rows in matrix = 1 (only one y variable exist in a Batch Evolution Model). Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedYPredPSOOCSum()

SQ_ErrorCode SQ_GetAlignedYPredPSOOCSum ( SQ_Prediction  pPrediction,
int  iComponent,
SQ_UnscaledState  bUnscaled,
SQ_BacktransformedState  bBackTransformed,
float  fHighLimit,
float  fLowLimit,
SQ_VectorData pVectorData 
)

Out Of Control for YPredPS

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]iComponentThe component in the model to get the result from.
[in]bUnscaledIf SQ_TRUE, the function will return the y-values in the (unscaled) metric of the dataset. If SQ_FALSE, the returned y-values will be in the scaled and centered metric of the workset. Note that if bBackTransformed is SQ_FALSE, the y-values will still be transformed. Note also that if bBackTransformed is SQ_TRUE, this parameter is ignored. In this case y-values will always be unscaled.
[in]bBackTransformedIf SQ_TRUE, the function will return the y-values in the unscaled untransformed metric of the workset. If SQ_FALSE the returned y-values will be transformed in the same way as the workset. Note that if this variable is SQ_TRUE, the returned y-values will always be unscaled irrespective of the value of bUnscaled.
[in]fHighLimitThe higher sigma limit.
[in]fLowLimitThe lower sigma limit.
[out]pVectorDataA pointer to the aligned YPredPS OOC results. Number of rows in matrix = 1. Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

◆ SQ_GetAlignedYVarPS()

SQ_ErrorCode SQ_GetAlignedYVarPS ( SQ_Prediction  pPrediction,
SQ_UnscaledState  bUnscaled,
SQ_BacktransformedState  bBackTransformed,
SQ_VectorData pVectorData 
)

Retrieves the aligned YVarPS matrix. The aligned time/maturity variable from the predictions. The function is only valid for a Batch Evolution model.

Parameters
[in]pPredictionThe handle to the predictions, is retrieved from GetBatchEvolutionPrediction()
[in]bUnscaledIf SQ_TRUE, the function will return the y-values in the (unscaled) metric of the dataset. If SQ_FALSE, the returned y-values will be in the scaled and centered metric of the workset. Note that if bBackTransformed is SQ_FALSE, the y-values will still be transformed. Note also that if bBackTransformed is SQ_TRUE, this parameter is ignored. In this case y-values will always be unscaled.
[in]bBackTransformedIf SQ_TRUE, the function will return the y-values in the unscaled untransformed metric of the workset. If SQ_FALSE the returned y-values will be transformed in the same way as the workset. Note that if this variable is SQ_TRUE, the returned y-values will always be unscaled irrespective of the value of bUnscaled.
[out]pVectorDataA pointer to the aligned YVarPS results. Number of rows in matrix = 1 (only one y variable exist in an observation level project). Number of columns in matrix = size of the aligned time or maturity vector.
Returns
Returns SQ_E_OK if success or an error code

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