{ "_id": "6ae45d6795ca2370cc8cf344", "Package": "nmfkc", "Type": "Package", "Title": "Non-Negative Matrix Factorization with Kernel Covariates", "Version": "1.0.2", "Date": "2026-10-29", "Authors@R": "person(\"Kenichi\", \"Satoh\",\nemail = \"kenichi-satoh@biwako.shiga-u.ac.jp\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-4436-9347\"))", "Maintainer": "Kenichi Satoh ", "URL": "https://github.com/ksatohds/nmfkc,\nhttps://ksatohds.github.io/nmfkc/", "BugReports": "https://github.com/ksatohds/nmfkc/issues", "Description": "Performs Non-negative Matrix Factorization (NMF) with\nKernel Covariates. Given an observation matrix and kernel\ncovariates, it optimizes both a basis matrix and a parameter\nmatrix. Notably, if the kernel matrix is an identity matrix,\nthe method simplifies to standard NMF. Also provides NMF with\nRandom Effects (NMF-RE) via nmfre(), which estimates a\nmixed-effects model combining covariate-driven scores with\nunit-specific random effects together with wild bootstrap\ninference, and NMF with feed-forward and feedback structure\n(NMF-FFB) via nmf.ffb(), which fits a two-block input-output\nmodel for blind source separation and path analysis.\nReferences: Satoh (2025) ; Satoh\n(2026) ; Satoh (2025)\n; Satoh (2026)\n; Satoh and Tokuda (2026)\n; Satoh (2026)\n.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Language": "en-US", "ByteCompile": "true", "VignetteBuilder": "knitr, rmarkdown", "Config/testthat/edition": "3", "Config/roxygen2/version": "8.0.0", "RoxygenNote": "7.2.3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-30 08:59:42 UTC", "User": "root" }, "Author": "Kenichi Satoh [aut, cre] (ORCID:\n)", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-10-30 07:17:39 UTC", "RemoteUrl": "https://github.com/cran/nmfkc", "RemoteRef": "HEAD", "RemoteSha": "c031c27836482a480de7fa32f6fa5c88f95641fb", "_user": "cran", "_type": "src", "_file": "nmfkc_1.0.2.tar.gz", "_fileid": "https://r2.ropensci.org/bc59ef17fa5a6d61346109811fea619f1e1c339fb1bed00763ee550a093f89d0", "_filesize": 1726045, "_sha256": "bc59ef17fa5a6d61346109811fea619f1e1c339fb1bed00763ee550a093f89d0", "_expires": "2027-02-07T09:03:32.000Z", "_created": "2026-10-30T08:59:42.000Z", "_published": "2026-10-30T09:03:34.854Z", "_upstream": "https://github.com/cran/nmfkc", "_status": "success", "_maintainer": { "name": "Kenichi Satoh", "email": "kenichi-satoh@biwako.shiga-u.ac.jp", "login": "ksatohds", "orcid": "0000-0003-4436-9347", "description": "Professor at Faculty of Data Science, Shiga University, JAPAN", "uuid": 141966099 }, "_jobs": [ { "job": 123978082289, "time": 145, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "12965606531" }, { "job": 123978082756, "time": 167, "config": 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"title": "Optimize kernel beta for nmfae by cross-validation", "topics": [ "nmf.rrr.kernel.beta.cv" ] }, { "page": "nmf.rrr.rank", "title": "Rank selection for nmfae (paired rank, concise diagnostics)", "topics": [ "nmf.rrr.rank" ] }, { "page": "nmf.rrr.rename", "title": "Rename decoder and encoder bases", "topics": [ "nmf.rrr.rename" ] }, { "page": "nmf.rrr.signed", "title": "Signed-Bottleneck NMF-AE: Three-Layer NMF-AE with Signed Bottleneck", "topics": [ "nmf.rrr.signed" ] }, { "page": "nmf.rrr.signed.ecv", "title": "Element-wise Cross-Validation for Signed-Bottleneck NMF-AE", "topics": [ "nmf.rrr.signed.ecv" ] }, { "page": "nmf.rrr.signed.heatmap", "title": "Heatmap visualization of nmfae.signed factor matrices", "topics": [ "nmf.rrr.signed.heatmap" ] }, { "page": "nmf.rrr.signed.inference", "title": "Statistical Inference for Signed-Bottleneck NMF-AE Signed Bottleneck", "topics": [ "nmf.rrr.signed.inference" ] }, { "page": "nmf.rrr.signed.rank", "title": "Rank selection for nmfae.signed (paired rank, concise diagnostics)", "topics": [ "nmf.rrr.signed.rank" ] }, { "page": "nmf.rrr.signed.rename", "title": "Rename Resp/Cov labels on nmfae.signed objects", "topics": [ "nmf.rrr.signed.rename" ] }, { "page": "nmfkc", "title": "Optimize NMF with kernel covariates (Full Support for Missing Values)", "topics": [ "nmfkc" ] }, { "page": "nmfkc.ar", "title": "Construct observation and covariate matrices for a vector autoregressive model", "topics": [ "nmfkc.ar" ] }, { "page": "nmfkc.ar.degree.cv", "title": "Optimize lag order for the autoregressive model", "topics": [ "nmfkc.ar.degree.cv" ] }, { "page": "nmfkc.ar.DOT", "title": "Generate a Graphviz DOT Diagram for NMF-AR / NMF-VAR Models", "topics": [ "nmfkc.ar.DOT" ] }, { "page": "nmfkc.ar.latent", "title": "Latent transition matrices of an NMF-VAR model", "topics": [ "nmfkc.ar.latent" ] }, { "page": "nmfkc.ar.latent.inference", "title": "Bootstrap inference for the latent VAR of an NMF-VAR model", "topics": [ 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"topics": [ "nmfkc.cv" ] }, { "page": "nmfkc.cv.methods", "title": "Print/plot methods for nmfkc cross-validation objects", "topics": [ "nmfkc.cv.methods", "plot.nmfkc.bicv", "plot.nmfkc.cv", "plot.nmfkc.ecv", "print.nmfkc.bicv", "print.nmfkc.cv", "print.nmfkc.ecv" ] }, { "page": "nmfkc.denormalize", "title": "Denormalize a matrix from [0,1] back to its original scale", "topics": [ "nmfkc.denormalize" ] }, { "page": "nmfkc.DOT", "title": "Generate Graphviz DOT Scripts for NMF or NMF-with-Covariates Models", "topics": [ "nmfkc.DOT" ] }, { "page": "nmfkc.ecv", "title": "Perform Element-wise Cross-Validation (Wold's CV)", "topics": [ "nmfkc.ecv" ] }, { "page": "nmfkc.inference", "title": "Statistical inference for the parameter matrix C (Theta)", "topics": [ "nmfkc.inference" ] }, { "page": "nmfkc.kernel", "title": "Create a kernel matrix from covariates", "topics": [ "nmfkc.kernel" ] }, { "page": "nmfkc.kernel.beta.cv", "title": "Optimize beta of the Gaussian kernel function by 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Parameters", "topics": [ "nmfkc.net.inference" ] }, { "page": "nmfkc.net.rank", "title": "Rank selection for nmfkc.net (concise diagnostics)", "topics": [ "nmfkc.net.rank" ] }, { "page": "nmfkc.normalize", "title": "Normalize a matrix to the range [0,1]", "topics": [ "nmfkc.normalize" ] }, { "page": "nmfkc.rank", "title": "Rank selection diagnostics with graphical output", "topics": [ "nmfkc.rank" ] }, { "page": "nmfkc.residual.plot", "title": "Plot Diagnostics: Original, Fitted, and Residual Matrices as Heatmaps", "topics": [ "nmfkc.residual.plot" ] }, { "page": "nmfkc.rff.beta.cv", "title": "Select the bandwidth of random-feature covariates by cross-validation", "topics": [ "nmfkc.rff.beta.cv" ] }, { "page": "nmfkc.rff.positive", "title": "Positive (non-negative) random features for the Gaussian kernel", "topics": [ "nmfkc.rff.positive" ] }, { "page": "nmfkc.rff.positive.gram", "title": "Block-wise Gram accumulation of positive random features for large N", "topics": [ "nmfkc.rff.positive.gram" ] }, { "page": "nmfkc.signed", "title": "NMF-KC with signed covariate matrix", "topics": [ "nmfkc.signed" ] }, { "page": "nmfkc.signed.cv", "title": "Column-wise k-fold cross-validation for nmfkc.signed", "topics": [ "nmfkc.signed.cv" ] }, { "page": "nmfkc.signed.ecv", "title": "Element-wise cross-validation for nmfkc.signed", "topics": [ "nmfkc.signed.ecv" ] }, { "page": "nmfkc.signed.rank", "title": "Rank selection for nmfkc.signed (concise diagnostics)", "topics": [ "nmfkc.signed.rank" ] }, { "page": "nmfkc.signed.rff", "title": "Random Fourier Features for nmfkc.signed()", "topics": [ "nmfkc.signed.rff" ] }, { "page": "nmfkc.signed.rff.gram", "title": "Block-wise Gram accumulation of Random Fourier Features for large N", "topics": [ "nmfkc.signed.rff.gram" ] }, { "page": "nmfre", "title": "Non-negative Matrix Factorization with Random Effects", "topics": [ "nmfre" ] }, { "page": "nmfre.ecv", "title": "NMF-RE element-wise cross-validation for rank selection", "topics": [ "nmfre.ecv" ] }, { "page": "nmfre.inference", "title": "Statistical inference for the coefficient matrix C from NMF-RE", "topics": [ "nmfre.inference" ] }, { "page": "plot.nmf.cluster.criteria", "title": "Plot clustering-quality criteria across a sequence of fits", "topics": [ "plot.nmf.cluster.criteria" ] }, { "page": "plot.nmf.cluster.flow", "title": "Plot a cluster-flow (alluvial) diagram", "topics": [ "plot.nmf.cluster.flow" ] }, { "page": "plot.nmf.gmm", "title": "Plot method for nmf.gmm objects", "topics": [ "plot.nmf.gmm" ] }, { "page": "plot.nmf.gmm.select", "title": "Plot method for nmf.gmm.select objects", "topics": [ "plot.nmf.gmm.select" ] }, { "page": "plot.nmf.rank", "title": "Plot a rank-selection (nmf.rank) object", "topics": [ "plot.nmf.rank" ] }, { "page": "plot.nmfae", "title": "'plot.nmfae' displays the convergence trajectory of the objective function across iterations. The title shows the achieved R^2.", "topics": [ "plot.nmfae" ] }, { "page": "plot.nmfkc", "title": "Plot method for objects of class 'nmfkc'", "topics": [ "plot.nmfkc" ] }, { "page": "plot.nmfkc.ar.latent", "title": "Plot the latent dynamics of an NMF-VAR model", "topics": [ "plot.nmfkc.ar.latent" ] }, { "page": "plot.nmfkc.ar.stationarity", "title": "Plot the stationarity bracket of an NMF-VAR model", "topics": [ "plot.nmfkc.ar.stationarity" ] }, { "page": "plot.nmfkc.ard", "title": "Plot method for nmfkc.ard objects", "topics": [ "plot.nmfkc.ard" ] }, { "page": "plot.nmfkc.consensus", "title": "Plot a consensus rank-selection (nmfkc.consensus) object", "topics": [ "plot.nmfkc.consensus" ] }, { "page": "plot.nmfkc.DOT", "title": "Plot method for nmfkc.DOT objects", "topics": [ "plot.nmfkc.DOT" ] }, { "page": "plot.nmfkc.signed", "title": "Plot method for nmfkc.signed (convergence)", "topics": [ "plot.nmfkc.signed" ] }, { "page": "plot.nmfre", "title": "Plot convergence diagnostics for NMF models", "topics": [ "plot.nmf.ffb", "plot.nmfre" ] }, { "page": "plot.nmfre.ecv", "title": "Plot method for nmfre.ecv objects", "topics": [ "plot.nmfre.ecv" ] }, { "page": "predict.nmf.gmm", "title": "Class assignments / responsibilities from an NMF-GMM fit", "topics": [ "predict.nmf.gmm" ] }, { "page": "predict.nmfkc", "title": "Prediction method for objects of class 'nmfkc'", "topics": [ "predict.nmfkc" ] }, { "page": "predict.nmfkc.signed", "title": "Predict method for nmfkc.signed", "topics": [ "predict.nmfkc.signed" ] }, { "page": "predict.nmfre", "title": "Predict method for nmfre objects", "topics": [ "predict.nmfre" ] }, { "page": "print.nmf", "title": "Print method for fitted NMF models", "topics": [ "print.nmf" ] }, { "page": "print.nmf.cluster.criteria", "title": "Print method for nmf.cluster.criteria objects", "topics": [ "print.nmf.cluster.criteria" ] }, { "page": "print.nmf.cluster.flow", "title": "Print method for nmf.cluster.flow objects", "topics": [ "print.nmf.cluster.flow" ] }, { "page": "print.nmf.ffb.test", "title": "Print a calibrated test of the feed-forward null", "topics": [ "print.nmf.ffb.test" ] }, { "page": "print.nmf.gmm", "title": "Print an NMF-GMM fit", "topics": [ "print.nmf.gmm" ] }, { "page": "print.nmf.gmm.select", "title": "Print method for nmf.gmm.select objects", "topics": [ "print.nmf.gmm.select" ] }, { "page": "print.nmf.inference", "title": "Print method for NMF inference objects", "topics": [ "print.nmf.inference" ] }, { "page": "print.nmf.rank", "title": "Print method for rank-selection (nmf.rank) objects", "topics": [ "print.nmf.rank" ] }, { "page": "print.nmfae.ecv", "title": "Print method for nmf.rrr element-wise CV results", "topics": [ "print.nmfae.ecv" ] }, { "page": "print.nmfkc.ar.latent", "title": "Print method for nmfkc.ar.latent objects", "topics": [ "print.nmfkc.ar.latent" ] }, { "page": "print.nmfkc.ar.latent.inference", "title": "Print method for nmfkc.ar.latent.inference objects", "topics": [ "print.nmfkc.ar.latent.inference" ] }, { "page": "print.nmfkc.ar.stationarity", "title": "Print method for nmfkc.ar.stationarity objects", "topics": [ "print.nmfkc.ar.stationarity" ] }, { "page": "print.nmfkc.ard", "title": "Print method for nmfkc.ard objects", "topics": [ "print.nmfkc.ard" ] }, { "page": "print.nmfkc.consensus", "title": "Print method for nmfkc.consensus objects", "topics": [ "print.nmfkc.consensus" ] }, { "page": "print.nmfkc.DOT", "title": "Print method for nmfkc.DOT objects", "topics": [ "print.nmfkc.DOT" ] }, { "page": "print.nmfkc.gram", "title": "Print method for nmfkc.gram", "topics": [ "print.nmfkc.gram" ] }, { "page": "print.nmfre.ecv", "title": "Print method for nmfre.ecv objects", "topics": [ "print.nmfre.ecv" ] }, { "page": "print.summary.nmf.ffb", "title": "Print method for summary.nmf.ffb objects", "topics": [ "print.summary.nmf.ffb" ] }, { "page": "print.summary.nmf.gmm", "title": "Print method for summary.nmf.gmm objects", "topics": [ "print.summary.nmf.gmm" ] }, { "page": "print.summary.nmfkc", "title": "Print method for 'summary.nmfkc' objects", "topics": [ "print.summary.nmfkc" ] }, { "page": "print.summary.nmfkc.inference", "title": "Print method for summary.nmfkc.inference objects", "topics": [ "print.summary.nmfkc.inference" ] }, { "page": "print.summary.nmfkc.net", "title": "Print method for summary.nmfkc.net objects", "topics": [ "print.summary.nmfkc.net" ] }, { "page": "print.summary.nmfkc.net.inference", "title": "Print method for summary.nmfkc.net.inference objects", "topics": [ "print.summary.nmfkc.net.inference" ] }, { "page": "print.summary.nmfkc.net.signed", "title": "Print method for summary.nmfkc.net.signed objects", "topics": [ "print.summary.nmfkc.net.signed" ] }, { "page": "print.summary.nmfkc.signed", "title": "Print method for summary.nmfkc.signed", "topics": [ "print.summary.nmfkc.signed" ] }, { "page": "residuals.nmf", "title": "Extract residuals from NMF models", "topics": [ "residuals.nmf", "residuals.nmf.ffb", "residuals.nmfae", "residuals.nmfre" ] }, { "page": "residuals.nmf.gmm", "title": "Residuals from an NMF-GMM fit", "topics": [ "residuals.nmf.gmm" ] }, { "page": "summary.nmf.ffb", "title": "Summary method for nmf.ffb objects", "topics": [ "summary.nmf.ffb" ] }, { "page": "summary.nmf.gmm", "title": "Summary of an NMF-GMM fit", "topics": [ "summary.nmf.gmm" ] }, { "page": "summary.nmfkc", "title": "Summary method for objects of class 'nmfkc'", "topics": [ "summary.nmfkc" ] }, { "page": "summary.nmfkc.inference", "title": "Summary method for nmfkc.inference objects", "topics": [ "summary.nmfkc.inference" ] }, { "page": "summary.nmfkc.net", "title": "Summary method for nmfkc.net objects", "topics": [ "summary.nmfkc.net" ] }, { "page": "summary.nmfkc.net.inference", "title": "Summary method for nmfkc.net.inference objects", "topics": [ "summary.nmfkc.net.inference" ] }, { "page": "summary.nmfkc.net.signed", "title": "Summary method for nmfkc.net.signed objects", "topics": [ "summary.nmfkc.net.signed" ] }, { "page": "summary.nmfkc.signed", "title": "Summary method for nmfkc.signed", "topics": [ "summary.nmfkc.signed" ] }, { "page": "summary.nmfre", "title": "Summary method for objects of class 'nmfre'", "topics": [ "print.summary.nmfre", "summary.nmfre" ] } ], "_readme": "https://github.com/cran/nmfkc/raw/HEAD/README.md", "_rundeps": [], "_vignettes": [ { "source": "introduction-to-nmfkc.Rmd", "filename": "introduction-to-nmfkc.html", "title": "Introduction to nmfkc", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "1. 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