{ "_id": "6ae70b092e87f76f20acc8a1", "Package": "funcharts", "Type": "Package", "Title": "Functional Control Charts", "Version": "1.8.1", "Authors@R": "c(\nperson(\"Christian\", \"Capezza\",\nemail = \"christian.capezza@unina.it\",\nrole = c(\"cre\",\"aut\")),\nperson(\"Fabio\", \"Centofanti\", role = c(\"aut\")),\nperson(\"Davide\", \"Forcina\", role = c(\"aut\")),\nperson(\"Antonio\", \"Lepore\", role = c(\"aut\")),\nperson(\"Biagio\", \"Palumbo\", role = c(\"aut\")),\nperson(\"Alessandra\", \"Menafoglio\", role = c(\"ctb\")),\nperson(\"Simone\", \"Vantini\", role = c(\"ctb\"))\n)", "Description": "Provides functional control charts for statistical process\nmonitoring of functional data, using the methods of Capezza et\nal. (2020) , Centofanti et al. (2021)\n, Capezza et al. (2024)\n, Capezza et al. (2024)\n, Centofanti et al. (2025)\n, Capezza et al. (2025)\n. The package is thoroughly\nillustrated in the paper of Capezza et al (2023)\n.", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "URL": "https://github.com/unina-sfere/funcharts", "BugReports": "https://github.com/unina-sfere/funcharts/issues", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-11-01 09:41:52 UTC", "User": "root" }, "Author": "Christian Capezza [cre, aut], Fabio Centofanti [aut], Davide\nForcina [aut], Antonio Lepore [aut], Biagio Palumbo [aut],\nAlessandra Menafoglio [ctb], Simone Vantini [ctb]", "Maintainer": "Christian Capezza ", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-01-18 23:40:09 UTC", "RemoteUrl": "https://github.com/cran/funcharts", "RemoteRef": "HEAD", "RemoteSha": "1bf52bc4f0b0fe2ea486245f78935cea7e12a329", "_user": "cran", "_type": "src", "_file": "funcharts_1.8.1.tar.gz", "_fileid": "https://r2.ropensci.org/bfb869269d88b3126d9c5f50fccdb9e5a947d74911bbb72b25329b7ca06ec65e", "_filesize": 1784588, "_sha256": "bfb869269d88b3126d9c5f50fccdb9e5a947d74911bbb72b25329b7ca06ec65e", "_expires": "2027-02-09T09:48:55.000Z", "_created": "2026-11-01T09:41:52.000Z", "_published": "2026-11-01T09:48:57.019Z", "_upstream": "https://github.com/cran/funcharts", "_status": "success", "_maintainer": { "name": "Christian Capezza", "email": "christian.capezza@unina.it", "login": "capezza", "linkedin": "in/christiancapezza", "description": "Assistant Professor of Statistics\nDepartment of Industrial Engineering\nUniversity of Naples Federico II", "uuid": 38164790 }, "_jobs": [ { "job": 124811808699, "time": 255, "config": "linux-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": "13078532153" }, { "job": 124811808750, "time": 279, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "13078832748" }, { "job": 124811808720, "time": 213, "config": "linux-release-arm64", "r": "4.6.2", "check": "OK", "artifact": "13078513406" }, { "job": 124811808703, "time": 269, "config": "linux-release-x86_64", "r": "4.6.2", "check": "OK", "artifact": "13078688365" }, { "job": 124810831256, "time": 282, "config": "source", "r": "4.6.2", "check": "OK", "artifact": "13078561763" }, { "job": 124811808704, "time": 144, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "13078892083" }, { "job": 124811808708, "time": 314, "config": "windows-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": "13078798044" }, { "job": 124811808694, "time": 264, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "13078806768" }, { "job": 124811808685, "time": 355, "config": "windows-release-arm64", "r": "4.6.2", "check": "OK", "artifact": "13078432442" }, { "job": 124811808706, "time": 218, "config": "windows-release-x86_64", "r": "4.6.2", "check": "OK", "artifact": "13078672060" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/41293941495", "_commit": { "id": "1bf52bc4f0b0fe2ea486245f78935cea7e12a329", "author": "Christian Capezza ", "committer": "cran-robot ", "message": "version 1.8.1\n", "time": 1768779609 }, "_distro": "resolute", "_host": "GitHub-Actions", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.6.0", "role": "Depends" }, { "package": "robustbase", "role": "Depends" }, { "package": "Rcpp", "role": "LinkingTo" }, { "package": "RcppArmadillo", "role": "LinkingTo" }, { "package": "dplyr", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "patchwork", "role": "Imports" }, { "package": "parallel", "role": "Imports" }, { "package": "tidyr", "role": "Imports" }, { "package": "Rcpp", "role": "Imports" }, { "package": "fda", "role": "Imports" }, { "package": "fda.usc", "role": "Imports" }, { "package": "roahd", "role": "Imports" }, { "package": "rrcov", "role": "Imports" }, { "package": "Rfast", "role": "Imports" }, { "package": "mgcv", "role": "Imports" }, { "package": "scam", "role": "Imports" }, { "package": "fdapace", "role": "Imports" }, { "package": "RSpectra", "role": "Imports" }, { "package": "MASS", "role": "Imports" }, { "package": "rofanova", "role": "Imports" }, { "package": "spatstat.univar", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "covr", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "testthat", "role": "Suggests" }, { "package": "sn", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 0, "_updates": [ { "week": "2025-50", "n": 1 }, { "week": "2026-03", "n": 1 } ], "_tags": [ { "name": "1.8.0", "date": "2025-12-12" }, { "name": "1.8.1", "date": "2026-01-18" } ], "_stars": 0, "_contributors": [ { "user": "capezza", "count": 13, "uuid": 38164790 } ], "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "followers": 635, "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 524, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/funcharts" }, "_devurl": "https://github.com/unina-sfere/funcharts", "_searchresults": 182, "_topics": [ "openblas", "cpp", "openmp" ], "_abi": { "exports": [], "imports": [ { "key": "Rcpp::Rcpp_precious_preserve()", "hash": "33a97ea62b293da6" }, { "key": "Rcpp::Rcpp_precious_remove()", "hash": "63d26947ba7e1377" }, { "key": "Rcpp::dataptr()", "hash": "54e69ad2e6668c83" }, { "key": "Rcpp::demangle()", "hash": "b0cfd6754c5ebc4e" }, { "key": "Rcpp::enterRNGScope()", "hash": "a04a299137cef947" }, { "key": "Rcpp::exitRNGScope()", "hash": "a04a299137cef947" }, { "key": "Rcpp::rcpp_get_stack_trace()", "hash": "c684a9bbe15cdc52" }, { "key": "Rcpp::rcpp_set_stack_trace()", "hash": "33a97ea62b293da6" } ] }, "_rbuild": "4.6.2", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/funcharts.html", "extra/manual.pdf", "extra/NEWS.html", "extra/NEWS.txt" ], "_homeurl": "https://github.com/unina-sfere/funcharts", "_realowner": "unina-sfere", "_cranurl": false, "_releases": [ { "version": "1.0.0", "date": "2021-03-15" }, { "version": "1.1.0", "date": "2021-10-01" }, { "version": "1.2.0", "date": "2022-06-15" }, { "version": "1.3.0", "date": "2023-02-13" }, { "version": "1.3.1", "date": "2023-02-20" }, { "version": "1.3.2", "date": "2023-09-05" }, { "version": "1.4.0", "date": "2024-02-15" }, { "version": "1.4.1", "date": "2024-02-22" }, { "version": "1.5.0", "date": "2024-07-19" }, { "version": "1.6.0", "date": "2024-12-11" }, { "version": "1.7.0", "date": "2025-03-17" }, { "version": "1.8.0", "date": "2025-12-12" }, { "version": "1.8.1", "date": "2026-01-18" } ], "_exports": [ "abline_mfd", "AMFCC_PhaseI", "AMFCC_PhaseII", "AMFEWMA_PhaseI", "AMFEWMA_PhaseII", "cbind_mfd", "cont_plot", "control_charts_pca", "control_charts_pca_mfd_real_time", "control_charts_sof_pc", "control_charts_sof_pc_real_time", "cor_mfd", "cov_mfd", "data_sim_mfd", "estimate_mixture", "FMRCC_PhaseI", "FMRCC_PhaseII", "fof_pc", "fof_pc_real_time", "FRTM_PhaseI", "FRTM_PhaseII", "functional_filter", "get_mfd_array", "get_mfd_array_real_time", "get_mfd_df", "get_mfd_df_real_time", "get_mfd_fd", "get_mfd_list", "get_mfd_list_real_time", "get_ooc", "get_outliers_mfd", "get_sof_pc_outliers", "inprod_mfd", "inprod_mfd_diag", "is.mfd", "lines_mfd", "mfd", "mFPCA", "minus_mfd", "nbasis", "norm.mfd", "nvar", "OEBFDTW", "par.FDTW", "par.mFPCA", "par.rtr", "pca_mfd", "pca_mfd_real_time", "plot_bifd", "plot_bootstrap_sof_pc", "plot_control_charts", "plot_control_charts_real_time", "plot_mfd", "plot_mon", "plot_pca_mfd", "plus_mfd", "predict_fof_pc", "predict_sof_pc", "rbind_mfd", "regr_cc_fof", "regr_cc_fof_real_time", "regr_cc_sof", "regr_cc_sof_real_time", "RoMFCC_PhaseI", "RoMFCC_PhaseII", "RoMFDI", "rpca_mfd", "scale_mfd", "sim_funcharts", "simulate_data_fmrcc", "simulate_data_FRTM", "simulate_data_RoMFCC", "simulate_mfd", "sof_pc", "sof_pc_real_time", "tensor_product_mfd", "times_mfd", "which_ooc" ], "_datasets": [ { "name": "air", "title": "Air quality data", "object": "air", "class": [ "list" ], "fields": [], "table": true, "tojson": true } ], "_help": [ { "page": "sub-.mfd", "title": "Extract observations and/or variables from 'mfd' objects.", "topics": [ "[.mfd" ] }, { "page": "abline_mfd", "title": "Add reference lines to all panels of the current multi-panel plot", "topics": [ "abline_mfd" ] }, { "page": "air", "title": "Air quality data", "topics": [ "air" ] }, { "page": "AMFCC_PhaseI", "title": "Phase I of the Adaptive Multivariate Functional Control Chart (AMFCC).", "topics": [ "AMFCC_PhaseI" ] }, { "page": "AMFCC_PhaseII", "title": "Phase II of the Adaptive Multivariate Functional Control Chart (AMFCC).", "topics": [ "AMFCC_PhaseII" ] }, { "page": "AMFEWMA_PhaseI", "title": "Adaptive Multivariate Functional EWMA control chart - Phase I", "topics": [ "AMFEWMA_PhaseI" ] }, { "page": "AMFEWMA_PhaseII", "title": "Adaptive Multivariate Functional EWMA control chart - Phase II", "topics": [ "AMFEWMA_PhaseII" ] }, { "page": "cbind_mfd", "title": "Bind variables of two Multivariate Functional Data Objects", "topics": [ "cbind_mfd" ] }, { "page": "cont_plot", "title": "Produce contribution plots", "topics": [ "cont_plot" ] }, { "page": "control_charts_pca", "title": "T2 and SPE control charts for multivariate functional data", "topics": [ "control_charts_pca" ] }, { "page": "control_charts_pca_mfd_real_time", "title": "Real-time T2 and SPE control charts for multivariate functional data", "topics": [ "control_charts_pca_mfd_real_time" ] }, { "page": "control_charts_sof_pc", "title": "Control charts for monitoring a scalar quality characteristic adjusted for by the effect of multivariate functional covariates", "topics": [ "control_charts_sof_pc" ] }, { "page": "control_charts_sof_pc_real_time", "title": "Real-time scalar-on-function regression control charts", "topics": [ "control_charts_sof_pc_real_time" ] }, { "page": "cor_mfd", "title": "Correlation Function for Multivariate Functional Data", "topics": [ "cor_mfd" ] }, { "page": "cov_mfd", "title": "Covariance Function for Multivariate Functional Data", "topics": [ "cov_mfd" ] }, { "page": "data_sim_mfd", "title": "Simulate multivariate functional data", "topics": [ "data_sim_mfd" ] }, { "page": "estimate_mixture", "title": "Performs the estimation of gaussian mixtures of regression models and gaussian mixture models. Used in FMRCC_PhaseI.", "topics": [ "estimate_mixture" ] }, { "page": "FMRCC_PhaseI", "title": "Phase I of the FMRCC", "topics": [ "FMRCC_PhaseI" ] }, { "page": "FMRCC_PhaseII", "title": "Phase II of the FMRCC", "topics": [ "FMRCC_PhaseII" ] }, { "page": "fof_pc", "title": "Function-on-function linear regression based on principal components", "topics": [ "fof_pc" ] }, { "page": "fof_pc_real_time", "title": "Get a list of function-on-function linear regression models estimated on functional data each evolving up to an intermediate domain point.", "topics": [ "fof_pc_real_time" ] }, { "page": "FRTM_PhaseI", "title": "Phase I of the FRTM method.", "topics": [ "FRTM_PhaseI" ] }, { "page": "FRTM_PhaseII", "title": "Phase II of the FRTM method.", "topics": [ "FRTM_PhaseII" ] }, { "page": "functional_filter", "title": "Finds functional componentwise outliers", "topics": [ "functional_filter" ] }, { "page": "get_mfd_array", "title": "Get Multivariate Functional Data from a three-dimensional array", "topics": [ "get_mfd_array" ] }, { "page": "get_mfd_array_real_time", "title": "Get a list of functional data objects each evolving up to an intermediate domain point.", "topics": [ "get_mfd_array_real_time" ] }, { "page": "get_mfd_df", "title": "Get Multivariate Functional Data from a data frame", "topics": [ "get_mfd_df" ] }, { "page": "get_mfd_df_real_time", "title": "Get a list of functional data objects each evolving up to an intermediate domain point.", "topics": [ "get_mfd_df_real_time" ] }, { "page": "get_mfd_fd", "title": "Convert a 'fd' object into a Multivariate Functional Data object.", "topics": [ "get_mfd_fd" ] }, { "page": "get_mfd_list", "title": "Get Multivariate Functional Data from a list of matrices", "topics": [ "get_mfd_list" ] }, { "page": "get_mfd_list_real_time", "title": "Get a list of functional data objects each evolving up to an intermediate domain point.", "topics": [ "get_mfd_list_real_time" ] }, { "page": "get_ooc", "title": "Get out of control observations from control charts", "topics": [ "get_ooc" ] }, { "page": "get_outliers_mfd", "title": "Get outliers from multivariate functional data", "topics": [ "get_outliers_mfd" ] }, { "page": "get_sof_pc_outliers", "title": "Get possible outliers of a training data set of a scalar-on-function regression model.", "topics": [ "get_sof_pc_outliers" ] }, { "page": "inprod_mfd", "title": "Inner products of functional data contained in 'mfd' objects.", "topics": [ "inprod_mfd" ] }, { "page": "inprod_mfd_diag", "title": "Inner product of two multivariate functional data objects, for each observation", "topics": [ "inprod_mfd_diag" ] }, { "page": "is.mfd", "title": "Confirm Object has Class 'mfd'", "topics": [ "is.mfd" ] }, { "page": "lines_mfd", "title": "Add the plot of a new multivariate functional data object to an existing plot.", "topics": [ "lines_mfd" ] }, { "page": "lines.mfd", "title": "Add curves to an existing multivariate functional data plot", "topics": [ "lines.mfd" ] }, { "page": "mean.mfd", "title": "Mean Function for Multivariate Functional Data", "topics": [ "mean.mfd" ] }, { "page": "mfd", "title": "Define a Multivariate Functional Data Object", "topics": [ "mfd" ] }, { "page": "mFPCA", "title": "Mixed Functional Principal Component Analysis (mFPCA)", "topics": [ "mFPCA" ] }, { "page": "minus_mfd", "title": "Subtract multivariate functional data (and unary negation)", "topics": [ "-.mfd", "minus_mfd" ] }, { "page": "mixregfit_multivariate", "title": "Performs the estimation of gaussian mixtures of regression models and gaussian mixture models. Used in FMRCC_PhaseI.", "topics": [ "mixregfit_multivariate" ] }, { "page": "nbasis", "title": "Number of basis functions", "topics": [ "nbasis" ] }, { "page": "nobs.mfd", "title": "Number of observations in a multivariate functional data object", "topics": [ "nobs.mfd" ] }, { "page": "norm.mfd", "title": "Norm of Multivariate Functional Data", "topics": [ "norm.mfd" ] }, { "page": "nvar", "title": "Number of variables", "topics": [ "nvar" ] }, { "page": "OEBFDTW", "title": "Open-end/open-begin Functional Dynamic Time Warping (OEB-FDTW)", "topics": [ "OEBFDTW" ] }, { "page": "par.FDTW", "title": "Setting open-end/open-begin functional dynamic time warping (OEB-FDTW) defaults", "topics": [ "par.FDTW" ] }, { "page": "par.mFPCA", "title": "Setting mixed functional principal component analysis (mFPCA) defaults", "topics": [ "par.mFPCA" ] }, { "page": "par.rtr", "title": "Setting real-time registration step defaults", "topics": [ "par.rtr" ] }, { "page": "pca_mfd", "title": "Multivariate functional principal components analysis", "topics": [ "pca_mfd" ] }, { "page": "pca_mfd_real_time", "title": "Get a list of multivariate functional principal component analysis models estimated on functional data each evolving up to an intermediate domain point.", "topics": [ "pca_mfd_real_time" ] }, { "page": "plot_bifd", "title": "Plot a Bivariate Functional Data Object.", "topics": [ "plot_bifd" ] }, { "page": "plot_bootstrap_sof_pc", "title": "Plot bootstrapped estimates of the scalar-on-function regression coefficient", "topics": [ "plot_bootstrap_sof_pc" ] }, { "page": "plot_control_charts", "title": "Plot control charts", "topics": [ "plot_control_charts" ] }, { "page": "plot_control_charts_real_time", "title": "Plot real-time control charts", "topics": [ "plot_control_charts_real_time" ] }, { "page": "plot_mfd", "title": "Plot a Multivariate Functional Data Object.", "topics": [ "plot_mfd" ] }, { "page": "plot_mon", "title": "Plot multivariate functional object over the training data set", "topics": [ "plot_mon" ] }, { "page": "plot_pca_mfd", "title": "Plot the harmonics of a 'pca_mfd' object", "topics": [ "plot_pca_mfd" ] }, { "page": "plot.AMFCC_PhaseI", "title": "Plot the results of the Phase I and the Phase II of the AMFCC", "topics": [ "plot.AMFCC_PhaseI", "plot.AMFCC_PhaseII" ] }, { "page": "plot.FRTM_PhaseI", "title": "Plot the results of the Phase I and the Phase II of the FRTM", "topics": [ "plot.FRTM_PhaseI", "plot.FRTM_PhaseII" ] }, { "page": "plot.mfd", "title": "Plot multivariate functional data", "topics": [ "plot.mfd" ] }, { "page": "plot.mFPCA", "title": "Plot the results of the Mixed Functional Principal Component Analysis (mFPCA)", "topics": [ "plot.mFPCA" ] }, { "page": "plus_mfd", "title": "Add multivariate functional data", "topics": [ "+.mfd", "plus_mfd" ] }, { "page": "predict_fof_pc", "title": "Use a function-on-function linear regression model for prediction", "topics": [ "predict_fof_pc" ] }, { "page": "predict_sof_pc", "title": "Use a scalar-on-function linear regression model for prediction", "topics": [ "predict_sof_pc" ] }, { "page": "predict.pca_mfd", "title": "Predict from a multivariate functional PCA", "topics": [ "predict.pca_mfd" ] }, { "page": "rbind_mfd", "title": "Bind replications of two Multivariate Functional Data Objects", "topics": [ "rbind_mfd" ] }, { "page": "regr_cc_fof", "title": "Functional Regression Control Chart", "topics": [ "regr_cc_fof" ] }, { "page": "regr_cc_fof_real_time", "title": "Real-time functional regression control chart", "topics": [ "regr_cc_fof_real_time" ] }, { "page": "regr_cc_sof", "title": "Scalar-on-Function Regression Control Chart", "topics": [ "regr_cc_sof" ] }, { "page": "regr_cc_sof_real_time", "title": "Real-time Scalar-on-Function Regression Control Chart", "topics": [ "regr_cc_sof_real_time" ] }, { "page": "RoAMFEWMA_PhaseI", "title": "Robust Adaptive Multivariate Functional EWMA Control Chart - Phase I", "topics": [ "RoAMFEWMA_PhaseI" ] }, { "page": "RoAMFEWMA_PhaseII", "title": "Robust Adaptive Multivariate Functional EWMA Control Chart - Phase II", "topics": [ "RoAMFEWMA_PhaseII" ] }, { "page": "RoMFCC_PhaseI", "title": "Robust Multivariate Functional Control Charts - Phase I", "topics": [ "RoMFCC_PhaseI" ] }, { "page": "RoMFCC_PhaseI_casewise", "title": "Robust Multivariate Functional Control Charts - Phase I (casewise version)", "topics": [ "RoMFCC_PhaseI_casewise" ] }, { "page": "RoMFCC_PhaseII", "title": "Robust Multivariate Functional Control Charts - Phase II", "topics": [ "RoMFCC_PhaseII" ] }, { "page": "RoMFCC_PhaseII_casewise", "title": "Robust Multivariate Functional Control Charts - Phase II (casewise version)", "topics": [ "RoMFCC_PhaseII_casewise" ] }, { "page": "RoMFDI", "title": "Robust Multivariate Functional Data Imputation (RoMFDI)", "topics": [ "RoMFDI" ] }, { "page": "rpca_mfd", "title": "Robust multivariate functional principal components analysis", "topics": [ "rpca_mfd" ] }, { "page": "scale_mfd", "title": "Standardize Multivariate Functional Data.", "topics": [ "scale_mfd" ] }, { "page": "sim_funcharts", "title": "Simulate example data for funcharts", "topics": [ "sim_funcharts" ] }, { "page": "simulate_data_fmrcc", "title": "Simulate Data for Functional Mixture Regression Control Chart (FMRCC)", "topics": [ "simulate_data_fmrcc" ] }, { "page": "simulate_data_FRTM", "title": "Simulate data for real-time monitoring of univariate functional data", "topics": [ "simulate_data_FRTM" ] }, { "page": "simulate_data_RoMFCC", "title": "Simulate multivariate functional data with casewise and componentwise contamination", "topics": [ "simulate_data_RoMFCC" ] }, { "page": "simulate_mfd", "title": "Simulate a data set for funcharts", "topics": [ "simulate_mfd" ] }, { "page": "sof_pc", "title": "Scalar-on-function linear regression based on principal components", "topics": [ "sof_pc" ] }, { "page": "sof_pc_real_time", "title": "Get a list of scalar-on-function linear regression models estimated on functional data each evolving up to an intermediate domain point.", "topics": [ "sof_pc_real_time" ] }, { "page": "tensor_product_mfd", "title": "Tensor product of two Multivariate Functional Data objects", "topics": [ "tensor_product_mfd" ] }, { "page": "times_mfd", "title": "Pointwise product of multivariate functional data (and scalar multiplication)", "topics": [ "*.mfd", "times_mfd" ] }, { "page": "which_ooc", "title": "Get the index of the out of control observations from control charts", "topics": [ "which_ooc" ] } ], "_rundeps": [ "abind", "ash", "askpass", "backports", "base64enc", "bslib", "cachem", "checkmate", "cli", "cluster", "codetools", "colorspace", "cpp11", "crosstalk", "curl", "data.table", "DEoptimR", "deSolve", "digest", "doParallel", "dplyr", "evaluate", "farver", "fastmap", "fda", "fda.usc", "fdapace", "fds", "FNN", "fontawesome", "foreach", "foreign", "Formula", "fs", "generics", "ggplot2", "glue", "gmp", "gridExtra", "gtable", "hdrcde", "highr", "Hmisc", "htmlTable", "htmltools", "htmlwidgets", "httr", "isoband", "iterators", "jquerylib", "jsonlite", "kernlab", "KernSmooth", "knitr", "ks", "kSamples", "labeling", "later", "lattice", "lazyeval", "lifecycle", "locfit", "magrittr", "MASS", "Matrix", "mclust", "memoise", "mgcv", "mime", "multicool", "mvtnorm", "nlme", "nnet", "numDeriv", "openssl", "otel", "patchwork", "pcaPP", "pillar", "pkgconfig", "plotly", "pracma", "promises", "purrr", "R6", "rainbow", "rappdirs", "RColorBrewer", "Rcpp", "RcppArmadillo", "RcppEigen", "RcppParallel", "Rfast", "rlang", "rmarkdown", "roahd", "robustbase", "rofanova", "rpart", "rrcov", "RSpectra", "rstudioapi", "S7", "sass", "scales", "scam", "spatstat.univar", "spatstat.utils", "stringi", "stringr", "SuppDists", "sys", "tibble", "tidyr", "tidyselect", "tinytex", "utf8", "vctrs", "viridisLite", "withr", "xfun", "yaml", "zigg" ], "_sysdeps": [ { "shlib": "liblapack", "package": "libopenblas0-pthread", "source": "openblas", "version": "0.3.32+ds-5", "name": "openblas", "homepage": "https://www.openblas.net/", "description": "Optimized BLAS (linear algebra) library (shared lib, pthread)" }, { "shlib": "libblas", "package": "libopenblas0-pthread", "source": "openblas", "version": "0.3.32+ds-5", "name": "openblas", "homepage": "https://www.openblas.net/", "description": "Optimized BLAS (linear algebra) library (shared lib, pthread)" }, { "shlib": "libstdc++", "package": "libstdc++6", "source": "gcc", "version": "16-20260322-1ubuntu1", "name": "c++", "homepage": "http://gcc.gnu.org/", "description": "GNU Standard C++ Library v3" }, { "shlib": "libgomp", "package": "libgomp1", "source": "gcc", "version": "16-20260322-1ubuntu1", "name": "openmp", "homepage": "http://gcc.gnu.org/", "description": "GCC OpenMP (GOMP) support library" } ], "_vignettes": [ { "source": "capezza2020.Rmd", "filename": "capezza2020.html", "title": "capezza2020", "engine": "knitr::rmarkdown", "headings": [ "Control charts for monitoring a scalar quality characteristic adjusted for by the effect of functional covariates", "Scalar-on-function regression", "Control charts", "References" ], "created": "2021-03-15 08:30:02", "modified": "2023-02-13 15:00:02", "commits": 4 }, { "source": "centofanti2021.Rmd", "filename": "centofanti2021.html", "title": "centofanti2021", "engine": "knitr::rmarkdown", "headings": [ "Functional Regression Control Chart", "Function-on-function regression based on principal components", "Plotting the functional regression control chart", "Real-time functional regression control chart", "References" ], "created": "2022-06-15 07:20:08", "modified": "2023-02-13 15:00:02", "commits": 2 }, { "source": "colosimo2010.Rmd", "filename": "colosimo2010.html", "title": "colosimo2010", "engine": "knitr::rmarkdown", "headings": [ "Functional control charts for multivariate quality characteristics", "Multivariate functional principal component analysis", "Control charts", "Fault detection", "References" ], "created": "2023-02-13 15:00:02", "modified": "2023-02-13 15:00:02", "commits": 1 }, { "source": "mfd.Rmd", "filename": "mfd.html", "title": "mfd", "engine": "knitr::rmarkdown", "headings": [ "The mfd class", "Getting multivariate functional data and the mfd class", "Plotting functions" ], "created": "2021-03-15 08:30:02", "modified": "2023-02-13 15:00:02", "commits": 2 } ], "_score": 4.163161374977018, "_indexed": false, "_nocasepkg": "funcharts", "_universes": [ "cran" ], "_indexurl": "https://unina-sfere.r-universe.dev/funcharts", "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.8.1", "date": "2026-11-01T09:44:53.000Z", "distro": "resolute", "arch": "aarch64", "commit": "1bf52bc4f0b0fe2ea486245f78935cea7e12a329", "fileid": "https://r2.ropensci.org/f9e41ee1f3e2446dfcbff2c65e853e194eb3ae59e34818662022b776b76f72e3", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41293941495" }, { "r": "4.7.0", "os": "linux", "version": "1.8.1", "date": "2026-11-01T09:44:43.000Z", "distro": "resolute", "arch": "x86_64", "commit": "1bf52bc4f0b0fe2ea486245f78935cea7e12a329", "fileid": "https://r2.ropensci.org/cdae9e93892a3610b1a4cda0322e7cf007b6468959b2046707c85f3f72006cd7", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41293941495" }, { "r": "4.6.2", "os": "linux", "version": "1.8.1", "date": "2026-11-01T09:44:18.000Z", "distro": "resolute", "arch": "aarch64", "commit": "1bf52bc4f0b0fe2ea486245f78935cea7e12a329", "fileid": "https://r2.ropensci.org/f27c0d0edd8b31e2f7da873b6c9d770f3e293c7674f1c3dda23f1134626cdbe7", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41293941495" }, { "r": "4.6.2", "os": "linux", "version": "1.8.1", "date": "2026-11-01T09:44:43.000Z", "distro": "resolute", "arch": "x86_64", "commit": "1bf52bc4f0b0fe2ea486245f78935cea7e12a329", "fileid": "https://r2.ropensci.org/1187d807b1a727f9d0caaf4701a4c8aa1241b9efdbde25ab1869193e825a5081", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41293941495" }, { "r": "4.6.0", "os": "wasm", "version": "1.8.1", "date": "2026-11-01T09:44:51.000Z", "arch": "emscripten", "commit": "1bf52bc4f0b0fe2ea486245f78935cea7e12a329", "fileid": "https://r2.ropensci.org/f86b401aebb6b9978f115100ef37559cd95c03f6e315a68396f9bc13187881a9", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/41293941495" }, { "r": "4.7.0", "os": "win", "version": "1.8.1", "date": "2026-11-01T09:45:14.000Z", "arch": "aarch64", "commit": "1bf52bc4f0b0fe2ea486245f78935cea7e12a329", "fileid": "https://r2.ropensci.org/ae75d8078cb597c3e0ccbd9d53c658db72464ab6e8284cf1d4e302600fbef7bd", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41293941495" }, { "r": "4.7.0", "os": "win", "version": "1.8.1", "date": "2026-11-01T09:43:46.000Z", "arch": "x86_64", "commit": "1bf52bc4f0b0fe2ea486245f78935cea7e12a329", "fileid": "https://r2.ropensci.org/1394e8ed04ecd5451762c0daf9ec331a6a925245844abe4e0079dd5f12100395", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41293941495" }, { "r": "4.6.2", "os": "win", "version": "1.8.1", "date": "2026-11-01T09:45:51.000Z", "arch": "aarch64", "commit": "1bf52bc4f0b0fe2ea486245f78935cea7e12a329", "fileid": "https://r2.ropensci.org/860981b269c3cd388a657e26174a0da52c0e43dacbd5d204a8177552fb105ea7", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41293941495" }, { "r": "4.6.2", "os": "win", "version": "1.8.1", "date": "2026-11-01T09:43:42.000Z", "arch": "x86_64", "commit": "1bf52bc4f0b0fe2ea486245f78935cea7e12a329", "fileid": "https://r2.ropensci.org/c97a073e8d8a04469c9ee8bded1f747e29091530ac7fa539f2a523fb013a6ad8", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/41293941495" } ] }