# Non-Negative Matrix Factorization with Kernel Covariates

## Documentation for package ‘nmfkc’ version 0.8.8

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

C F N P R S

## -- C --

coef.nmf | Extract coefficients from NMF models
coef.nmf.sem | Extract coefficients from NMF models

## -- F --

fitted.nmf | Extract fitted values from NMF models
fitted.nmf.sem | Extract fitted values from NMF models
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 Main Estimation Algorithm (formerly NMF-SEM)
nmf.ffb.cv | Cross-Validation for NMF-FFB
nmf.ffb.DOT | Generate a Graphviz DOT Diagram for an NMF-FFB Model
nmf.ffb.inference | Statistical inference for NMF-FFB via X-fixed full pair bootstrap
nmf.ffb.split | Heuristic Variable Splitting for NMF-FFB
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.predict | Forecast future values for NMF-VAR model
nmfkc.ar.stationarity | Check 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.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.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()
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.rank | Plot a rank-selection (nmf.rank) object
plot.nmf.sem | Plot convergence diagnostics for NMF models
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.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.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.cluster.criteria | Print method for nmf.cluster.criteria objects
print.nmf.cluster.flow | Print method for nmf.cluster.flow objects
print.nmf.inference | Print method for NMF inference objects
print.nmf.rank | Print method for rank-selection (nmf.rank) 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.ecv | Print/plot methods for nmfkc cross-validation objects
print.nmfre.ecv | Print method for nmfre.ecv objects
print.summary.nmf.sem | Print method for summary.nmf.sem 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

## -- R --

residuals.nmf | Extract residuals from NMF models
residuals.nmf.sem | Extract residuals from NMF models
residuals.nmfae | Extract residuals from NMF models
residuals.nmfre | Extract residuals from NMF models

## -- S --

summary.nmf.sem | Summary method for nmf.sem objects
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'