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MFAIR-class
- Each MFAIR object has a number of slots which store information. Key slots to access are listed below.
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MFAIRSingleFactor-class
- MFAIRSingleFactor object contains the key information about the fitted single factor MFAI model.
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appendMFAIR()
- Append the fitted factor to the MFAIR object in the greedy algorithm.
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createMFAIR()
- Create the MFAIR object with main data matrix and auxiliary information.
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fitBack()
- Fit the MFAI model using backfitting algorithm.
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fitGreedy()
- Fit the MFAI model using greedy algorithm.
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fitSFFully()
- Fit the single factor MFAI model with fully observed main data matrix.
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fitSFMissing()
- Fit the single factor MFAI model with partially observed main data matrix.
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fitSFSparse()
- Fit the single factor MFAI model with partially observed main data matrix stored in the sparse mode.
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getELBO()
- Compute the evidence lower bound (ELBO) for fitted single factor MFAI model.
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getImportance()
- Get importance measures of auxiliary covariates.
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getImportanceSF()
- Get importance measures of auxiliary covariates in a single factor.
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initSF()
- Initialize the parameters for the single factor MAFI model.
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matrixORdgCMatrix-class
- Define the matrixORdgCMatrix class as the union of matrix and Matrix::dgCMatrix.
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ml100k
- MovieLens 100K data.
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neocortex
- Human brain gene expression data.
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predict(<MFAIR>)
- Prediction function for MFAIR object.
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predict(<MFAIRSingleFactor>)
- Prediction function for MFAIRSingleFactor object.
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predictFX()
- Prediction function for fitted functions.
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predictFXSF()
- Prediction function for fitted function F() in single factor.
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projSparse()
- Project a matrix with given indices and store the result in the sparse mode.
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updateMFAIR()
- Update the k-th factor of the MFAIR object in the backfitting algorithm.