Non-Negative Matrix Factorization with Kernel Covariates
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Documentation for package ‘nmfkc’ version 0.7.3
Help Pages
| coef.nmf | Extract coefficients from NMF models |
| coef.nmf.sem | Extract coefficients from NMF models |
| 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 |
| 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.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.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.class | Create a class (one-hot) matrix from a categorical vector |
| 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.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 |
| 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 |
| 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.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.inference | Print method for NMF inference 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 |
| 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 |
| 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' |