Non-Negative Matrix Factorization with Kernel Covariates
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Documentation for package ‘nmfkc’ version 0.9.8
Help Pages
-- C --
| coef.nmf | Extract coefficients from NMF models |
| coef.nmf.ffb | Extract coefficients from NMF models |
| coef.nmf.gmm | Extract the covariate-coefficient matrix from an NMF-GMM fit |
-- F --
| fitted.nmf | Extract fitted values from NMF models |
| fitted.nmf.ffb | Extract fitted values from NMF models |
| fitted.nmf.gmm | Fitted (responsibility-averaged) reconstruction of an NMF-GMM fit |
| fitted.nmfae | Extract fitted values from NMF models |
| fitted.nmfre | Extract fitted values from NMF models |
-- N --
| nmf.cluster.criteria | Sample-clustering quality across ranks |
| nmf.cluster.flow | Cluster-flow (alluvial) diagram across a sequence of fits |
| nmf.ffb | NMF-FFB: non-negative matrix factorization with latent feedback |
| nmf.ffb.cv | Cross-Validation for NMF-FFB |
| nmf.ffb.diagnostics | Structural Diagnostics of a Fitted NMF-FFB Feedback Matrix |
| nmf.ffb.DOT | Generate a Graphviz DOT Diagram for an NMF-FFB Model |
| nmf.ffb.ecv | Choose the number of factors for NMF-FFB by element-wise cross-validation |
| nmf.ffb.inference | Bootstrap inference for NMF-FFB (X held fixed) |
| nmf.ffb.split | Heuristic Variable Splitting for NMF-FFB |
| nmf.ffb.test | Test the feed-forward null of an NMF-FFB fit |
| nmf.gmm | Fit NMF-GMM: a Gaussian-mixture latent-class extension of NMF with covariates |
| nmf.gmm.inference | Statistical inference for an NMF-GMM fit (given basis) |
| nmf.gmm.select | Choose the number of mixture components K for NMF-GMM |
| nmf.gmm.twostage | Two-stage (adjust-then-cluster) baseline for NMF-GMM |
| nmf.rrr | Three-Layer Non-negative Matrix Factorization (NMF-AE) |
| nmf.rrr.cv | Sample-wise k-fold Cross-Validation for nmfae |
| nmf.rrr.DOT | DOT graph visualization for nmfae objects |
| nmf.rrr.ecv | Element-wise Cross-Validation for nmfae (Wold's CV) |
| nmf.rrr.heatmap | Heatmap visualization of nmfae factor matrices |
| nmf.rrr.inference | Statistical Inference for NMF-AE Parameter Matrix |
| nmf.rrr.kernel.beta.cv | Optimize kernel beta for nmfae by cross-validation |
| nmf.rrr.rank | Rank selection for nmfae (paired rank, concise diagnostics) |
| nmf.rrr.rename | Rename decoder and encoder bases |
| nmf.rrr.signed | Signed-Bottleneck NMF-AE: Three-Layer NMF-AE with Signed Bottleneck |
| nmf.rrr.signed.ecv | Element-wise Cross-Validation for Signed-Bottleneck NMF-AE |
| nmf.rrr.signed.heatmap | Heatmap visualization of nmfae.signed factor matrices |
| nmf.rrr.signed.inference | Statistical Inference for Signed-Bottleneck NMF-AE Signed Bottleneck |
| nmf.rrr.signed.rank | Rank selection for nmfae.signed (paired rank, concise diagnostics) |
| nmf.rrr.signed.rename | Rename Resp/Cov labels on nmfae.signed objects |
| nmfkc | Optimize NMF with kernel covariates (Full Support for Missing Values) |
| nmfkc.ar | Construct observation and covariate matrices for a vector autoregressive model |
| nmfkc.ar.degree.cv | Optimize lag order for the autoregressive model |
| nmfkc.ar.DOT | Generate a Graphviz DOT Diagram for NMF-AR / NMF-VAR Models |
| nmfkc.ar.latent | Latent transition matrices of an NMF-VAR model |
| nmfkc.ar.latent.inference | Bootstrap inference for the latent VAR of an NMF-VAR model |
| nmfkc.ar.predict | Forecast future values for NMF-VAR model |
| nmfkc.ar.stationarity | Stationarity of an NMF-VAR model |
| nmfkc.ard | Automatic relevance determination for NMF rank (experimental) |
| nmfkc.bicv | Bi-cross-validation for NMF rank selection |
| nmfkc.class | Create a class (one-hot) matrix from a categorical vector |
| nmfkc.consensus | Consensus-clustering rank selection for NMF (Brunet 2004) |
| nmfkc.criterion | Compute model selection criteria for a fitted nmfkc model |
| nmfkc.cv | Perform k-fold cross-validation for NMF with kernel covariates |
| nmfkc.cv.methods | Print/plot methods for nmfkc cross-validation objects |
| nmfkc.denormalize | Denormalize a matrix from [0,1] back to its original scale |
| nmfkc.DOT | Generate Graphviz DOT Scripts for NMF or NMF-with-Covariates Models |
| nmfkc.ecv | Perform Element-wise Cross-Validation (Wold's CV) |
| nmfkc.inference | Statistical inference for the parameter matrix C (Theta) |
| nmfkc.kernel | Create a kernel matrix from covariates |
| nmfkc.kernel.beta.cv | Optimize beta of the Gaussian kernel function by cross-validation |
| nmfkc.kernel.beta.nearest.med | Estimate Gaussian/RBF kernel parameter beta from covariates (supports landmarks) |
| nmfkc.kernel.gaussian | Create a Gaussian kernel matrix from covariates |
| nmfkc.kernel.gram | Block-wise Gram accumulation of Nystroem kernel covariates for large N |
| nmfkc.net | Symmetric NMF for networks (tri / bi / signed) |
| nmfkc.net.DOT | Generate a Graphviz DOT Diagram for a Symmetric NMF Network |
| nmfkc.net.ecv | Element-wise cross-validation for nmfkc.net (upper-triangle folds) |
| nmfkc.net.inference | Statistical Inference for Symmetric NMF Parameters |
| nmfkc.net.rank | Rank selection for nmfkc.net (concise diagnostics) |
| nmfkc.normalize | Normalize a matrix to the range [0,1] |
| nmfkc.rank | Rank selection diagnostics with graphical output |
| nmfkc.residual.plot | Plot Diagnostics: Original, Fitted, and Residual Matrices as Heatmaps |
| nmfkc.rff.beta.cv | Select the bandwidth of random-feature covariates by cross-validation |
| nmfkc.rff.positive | Positive (non-negative) random features for the Gaussian kernel |
| nmfkc.rff.positive.gram | Block-wise Gram accumulation of positive random features for large N |
| nmfkc.signed | NMF-KC with signed covariate matrix |
| nmfkc.signed.cv | Column-wise k-fold cross-validation for nmfkc.signed |
| nmfkc.signed.ecv | Element-wise cross-validation for nmfkc.signed |
| nmfkc.signed.rank | Rank selection for nmfkc.signed (concise diagnostics) |
| nmfkc.signed.rff | Random Fourier Features for nmfkc.signed() |
| nmfkc.signed.rff.gram | Block-wise Gram accumulation of Random Fourier Features for large N |
| nmfre | Non-negative Matrix Factorization with Random Effects |
| nmfre.ecv | NMF-RE element-wise cross-validation for rank selection |
| nmfre.inference | Statistical inference for the coefficient matrix C from NMF-RE |
-- P --
| plot.nmf.cluster.criteria | Plot clustering-quality criteria across a sequence of fits |
| plot.nmf.cluster.flow | Plot a cluster-flow (alluvial) diagram |
| plot.nmf.ffb | Plot convergence diagnostics for NMF models |
| plot.nmf.gmm | Plot method for nmf.gmm objects |
| plot.nmf.gmm.select | Plot method for nmf.gmm.select objects |
| plot.nmf.rank | Plot a rank-selection (nmf.rank) object |
| plot.nmfae | 'plot.nmfae' displays the convergence trajectory of the objective function across iterations. The title shows the achieved R^2. |
| plot.nmfkc | Plot method for objects of class 'nmfkc' |
| plot.nmfkc.ar.latent | Plot the latent dynamics of an NMF-VAR model |
| plot.nmfkc.ar.stationarity | Plot the stationarity bracket of an NMF-VAR model |
| plot.nmfkc.ard | Plot method for nmfkc.ard objects |
| plot.nmfkc.bicv | Print/plot methods for nmfkc cross-validation objects |
| plot.nmfkc.consensus | Plot a consensus rank-selection (nmfkc.consensus) object |
| plot.nmfkc.cv | Print/plot methods for nmfkc cross-validation objects |
| plot.nmfkc.DOT | Plot method for nmfkc.DOT objects |
| plot.nmfkc.ecv | Print/plot methods for nmfkc cross-validation objects |
| plot.nmfkc.signed | Plot method for nmfkc.signed (convergence) |
| plot.nmfre | Plot convergence diagnostics for NMF models |
| plot.nmfre.ecv | Plot method for nmfre.ecv objects |
| predict.nmf.gmm | Class assignments / responsibilities from an NMF-GMM fit |
| predict.nmfkc | Prediction method for objects of class 'nmfkc' |
| predict.nmfkc.signed | Predict method for nmfkc.signed |
| predict.nmfre | Predict method for nmfre objects |
| print.nmf | Print method for fitted NMF models |
| print.nmf.cluster.criteria | Print method for nmf.cluster.criteria objects |
| print.nmf.cluster.flow | Print method for nmf.cluster.flow objects |
| print.nmf.ffb.test | Print a calibrated test of the feed-forward null |
| print.nmf.gmm | Print an NMF-GMM fit |
| print.nmf.gmm.select | Print method for nmf.gmm.select objects |
| print.nmf.inference | Print method for NMF inference objects |
| print.nmf.rank | Print method for rank-selection (nmf.rank) objects |
| print.nmfae.ecv | Print method for nmf.rrr element-wise CV results |
| print.nmfkc.ar.latent | Print method for nmfkc.ar.latent objects |
| print.nmfkc.ar.latent.inference | Print method for nmfkc.ar.latent.inference objects |
| print.nmfkc.ar.stationarity | Print method for nmfkc.ar.stationarity objects |
| print.nmfkc.ard | Print method for nmfkc.ard objects |
| print.nmfkc.bicv | Print/plot methods for nmfkc cross-validation objects |
| print.nmfkc.consensus | Print method for nmfkc.consensus objects |
| print.nmfkc.cv | Print/plot methods for nmfkc cross-validation objects |
| print.nmfkc.DOT | Print method for nmfkc.DOT objects |
| print.nmfkc.ecv | Print/plot methods for nmfkc cross-validation objects |
| print.nmfkc.gram | Print method for nmfkc.gram |
| print.nmfre.ecv | Print method for nmfre.ecv objects |
| print.summary.nmf.ffb | Print method for summary.nmf.ffb objects |
| print.summary.nmf.gmm | Print method for summary.nmf.gmm objects |
| print.summary.nmfkc | Print method for 'summary.nmfkc' objects |
| print.summary.nmfkc.inference | Print method for summary.nmfkc.inference objects |
| print.summary.nmfkc.net | Print method for summary.nmfkc.net objects |
| print.summary.nmfkc.net.inference | Print method for summary.nmfkc.net.inference objects |
| print.summary.nmfkc.net.signed | Print method for summary.nmfkc.net.signed objects |
| print.summary.nmfkc.signed | Print method for summary.nmfkc.signed |
| print.summary.nmfre | Summary method for objects of class 'nmfre' |
-- R --
| residuals.nmf | Extract residuals from NMF models |
| residuals.nmf.ffb | Extract residuals from NMF models |
| residuals.nmf.gmm | Residuals from an NMF-GMM fit |
| residuals.nmfae | Extract residuals from NMF models |
| residuals.nmfre | Extract residuals from NMF models |
-- S --
| summary.nmf.ffb | Summary method for nmf.ffb objects |
| summary.nmf.gmm | Summary of an NMF-GMM fit |
| summary.nmfkc | Summary method for objects of class 'nmfkc' |
| summary.nmfkc.inference | Summary method for nmfkc.inference objects |
| summary.nmfkc.net | Summary method for nmfkc.net objects |
| summary.nmfkc.net.inference | Summary method for nmfkc.net.inference objects |
| summary.nmfkc.net.signed | Summary method for nmfkc.net.signed objects |
| summary.nmfkc.signed | Summary method for nmfkc.signed |
| summary.nmfre | Summary method for objects of class 'nmfre' |