Non-Negative Matrix Factorization with Kernel Covariates


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Documentation for package ‘nmfkc’ version 0.8.2

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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

-- 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.sem NMF-FFB Main Estimation Algorithm (formerly NMF-SEM)
nmf.sem.cv Cross-Validation for NMF-FFB
nmf.sem.DOT Generate a Graphviz DOT Diagram for an NMF-FFB Model
nmf.sem.inference Statistical inference for NMF-FFB via X-fixed full pair bootstrap
nmf.sem.split Heuristic Variable Splitting for NMF-FFB
nmfae Three-Layer Non-negative Matrix Factorization (NMF-AE)
nmfae.cv Sample-wise k-fold Cross-Validation for nmfae
nmfae.DOT DOT graph visualization for nmfae objects
nmfae.ecv Element-wise Cross-Validation for nmfae (Wold's CV)
nmfae.heatmap Heatmap visualization of nmfae factor matrices
nmfae.inference Statistical Inference for NMF-AE Parameter Matrix
nmfae.kernel.beta.cv Optimize kernel beta for nmfae by cross-validation
nmfae.rank Rank selection for nmfae (paired rank, concise diagnostics)
nmfae.rename Rename decoder and encoder bases
nmfae.signed Signed-Bottleneck NMF-AE: Three-Layer NMF-AE with Signed Bottleneck
nmfae.signed.ecv Element-wise Cross-Validation for Signed-Bottleneck NMF-AE
nmfae.signed.heatmap Heatmap visualization of nmfae.signed factor matrices
nmfae.signed.inference Statistical Inference for Signed-Bottleneck NMF-AE Signed Bottleneck
nmfae.signed.rank Rank selection for nmfae.signed (paired rank, concise diagnostics)
nmfae.signed.rename Rename Dec/Enc 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.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.dfU.scan Scan dfU cap rates for NMF-RE
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.nmfae.cv Plot method for nmfae.cv objects
plot.nmfae.ecv Plot method for nmfae.ecv objects
plot.nmfae.kernel.beta.cv Plot method for nmfae.kernel.beta.cv objects
plot.nmfae.signed Plot method for nmfae.signed (convergence)
plot.nmfkc Plot method for objects of class 'nmfkc'
plot.nmfkc.ard Plot method for nmfkc.ard objects
plot.nmfkc.consensus Plot a consensus rank-selection (nmfkc.consensus) object
plot.nmfkc.DOT Plot method for nmfkc.DOT objects
plot.nmfkc.signed Plot method for nmfkc.signed (convergence)
plot.nmfre Plot convergence diagnostics for NMF models
plot.predict.nmfae Plot method for predict.nmfae objects
predict.nmfae Predict method for nmfae objects
predict.nmfae.signed Predict method for nmfae.signed
predict.nmfkc Prediction method for objects of class 'nmfkc'
predict.nmfkc.signed Predict method for nmfkc.signed
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.consensus Print method for nmfkc.consensus objects
print.summary.nmf.sem Print method for summary.nmf.sem objects
print.summary.nmfae Print method for summary.nmfae objects
print.summary.nmfae.inference Print method for summary.nmfae.inference objects
print.summary.nmfae.signed Print method for summary.nmfae.signed
print.summary.nmfae.signed.inference Print method for summary.nmfae.signed.inference 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.nmfae Summary method for nmfae objects
summary.nmfae.inference Summary method for nmfae.inference objects
summary.nmfae.signed Summary method for nmfae.signed
summary.nmfae.signed.inference Summary method for nmfae.signed.inference 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'