{ "_id": "6a1538d8acfb0bcc41d50140", "Package": "ftsa", "Type": "Package", "Title": "Functional Time Series Analysis", "Version": "6.7", "Date": "2026-03-31", "LazyLoad": "yes", "LazyData": "yes", "LazyDataCompression": "xz", "ByteCompile": "TRUE", "Authors@R": "c(\nperson(\"Rob\", \"Hyndman\", role=\"aut\", comment = c(ORCID = \"0000-0002-2140-5352\")),\nperson(\"Han Lin\", \"Shang\", email=\"hanlin.shang@mq.edu.au\", role=c(\"aut\", \"cre\", \"cph\"), comment = c(ORCID = \"0000-0003-1769-6430\"))\n)", "Maintainer": "Han Lin Shang ", "Description": "Functions for visualizing, modeling, forecasting and\nhypothesis testing of functional time series.", "License": "GPL-3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-26 06:03:45 UTC", "User": "root" }, "Author": "Rob Hyndman [aut] (ORCID:\n), Han Lin Shang [aut,\ncre, cph] (ORCID: )", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-03-31 07:47:28 UTC", "RemoteUrl": "https://github.com/cran/ftsa", "RemoteRef": "HEAD", "RemoteSha": "ff39696f94dd5f9067e188712ba59b63f1ee40c3", "MD5sum": "ae27d08436e02495239fe65416b7477c", "_user": "cran", "_type": "src", "_file": "ftsa_6.7.tar.gz", "_fileid": "a178e8780e6530bc88b32dcfb25e33f2b70e0ee784966eb78a75ceb30dbef0a2", "_filesize": 591024, "_sha256": "a178e8780e6530bc88b32dcfb25e33f2b70e0ee784966eb78a75ceb30dbef0a2", "_created": "2026-05-26T06:03:45.000Z", "_published": "2026-05-26T06:08:24.140Z", "_distro": "noble", "_jobs": [ { "job": 77816768743, "time": 227, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7210023665" }, { "job": 77816768769, "time": 230, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7210024238" }, { "job": 77816276982, "time": 260, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7209974199" }, { "job": 77816768749, "time": 156, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7210008386" } ], "_buildurl": "https://github.com/r-universe/cran/actions/runs/26435082509", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/ftsa", "_commit": { "id": "ff39696f94dd5f9067e188712ba59b63f1ee40c3", "author": "Han Lin Shang ", "committer": "cran-robot ", "message": "version 6.7\n", "time": 1774943248 }, "_maintainer": { "name": "Han Lin Shang", "email": "hanlin.shang@mq.edu.au", "orcid": "0000-0003-1769-6430" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 3.5.0", "role": "Depends" }, { "package": "forecast", "role": "Depends" }, { "package": "rainbow", "role": "Depends" }, { "package": "sde", "role": "Depends" }, { "package": "colorspace", "role": "Imports" }, { "package": "MASS", "role": "Imports" }, { "package": "pcaPP", "role": "Imports" }, { "package": "fda", "role": "Imports" }, { "package": "pdfCluster", "role": "Imports" }, { "package": "ecp", "role": "Imports" }, { "package": "strucchange", "role": "Imports" }, { "package": "e1071", "role": "Imports" }, { "package": "psych", "role": "Imports" }, { "package": "fGarch", "role": "Imports" }, { "package": "KernSmooth", "role": "Imports" }, { "package": "vars", "role": "Imports" }, { "package": "boot", "role": "Imports" }, { "package": "fdapace", "role": "Imports" }, { "package": "LaplacesDemon", "role": "Imports" }, { "package": "evgam", "role": "Imports" }, { "package": "ROOPSD", "role": "Imports" }, { "package": "glue", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "fds", "role": "Suggests" }, { "package": "R2jags", "role": "Suggests" }, { "package": "meboot", "role": "Suggests" } ], "_owner": "cran", "_selfowned": false, "_usedby": 12, "_updates": [ { "week": "2026-14", "n": 1 } ], "_tags": [ { "name": "6.7", "date": "2026-03-31" } ], "_stars": 6, "_userbio": { "uuid": 6899542, "type": "organization", "name": "cran", "description": "Unofficial read-only mirror of all CRAN R packages" }, "_downloads": { "count": 5464, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/ftsa" }, "_searchresults": 90, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/ftsa.html", "manual.pdf" ], "_realowner": "cran", "_cranurl": false, "_releases": [ { "version": "1.0", "date": "2009-09-12" }, { "version": "1.1", "date": "2009-10-08" }, { "version": "1.2", "date": "2009-12-09" }, { "version": "1.3", "date": "2009-12-20" }, { "version": "1.4", "date": "2010-02-12" }, { "version": "1.5", "date": "2010-02-22" }, { "version": "1.6", "date": "2010-03-15" }, { "version": "1.7", "date": "2010-05-16" }, { "version": "1.8", "date": "2010-06-04" }, { "version": "1.9", "date": "2010-06-08" }, { "version": "2.0", "date": "2010-10-14" }, { "version": "2.1", "date": "2010-11-09" }, { "version": "2.2", "date": "2010-11-19" }, { "version": "2.3", "date": "2010-12-07" }, { "version": "2.4", "date": "2010-12-09" }, { "version": "2.5", "date": "2011-01-03" }, { "version": "2.6", "date": "2011-03-31" }, { "version": "2.7", "date": "2011-09-14" }, { "version": "2.8", "date": "2012-01-06" }, { "version": "2.9", "date": "2012-01-08" }, { "version": "3.0", "date": "2012-01-20" }, { "version": "3.1", "date": "2012-02-01" }, { "version": "3.2", "date": "2012-05-21" }, { "version": "3.3", "date": "2012-05-28" }, { "version": "3.4", "date": "2012-07-29" }, { "version": "3.5", "date": "2012-09-13" }, { "version": "3.6", "date": "2012-10-24" }, { "version": "3.7", "date": "2013-02-21" }, { "version": "3.8", "date": "2013-04-05" }, { "version": "3.9", "date": "2013-08-29" }, { "version": "4.0", "date": "2014-06-23" }, { "version": "4.1", "date": "2014-12-10" }, { "version": "4.2", "date": "2015-03-12" }, { "version": "4.3", "date": "2015-03-30" }, { "version": "4.4", "date": "2015-08-05" }, { "version": "4.5", "date": "2015-11-12" }, { "version": "4.6", "date": "2015-12-23" }, { "version": "4.7", "date": "2016-03-15" }, { "version": "4.8", "date": "2017-04-25" }, { "version": "4.9", "date": "2018-08-23" }, { "version": "5.0", "date": "2018-09-15" }, { "version": "5.1", "date": "2018-10-07" }, { "version": "5.2", "date": "2018-11-01" }, { "version": "5.3", "date": "2019-01-03" }, { "version": "5.4", "date": "2019-01-30" }, { "version": "5.5", "date": "2019-04-21" }, { "version": "5.6", "date": "2020-04-23" }, { "version": "5.7", "date": "2020-05-18" }, { "version": "5.8", "date": "2020-06-15" }, { "version": "5.9", "date": "2020-09-25" }, { "version": "6.0", "date": "2020-11-29" }, { "version": "6.1", "date": "2021-11-02" }, { "version": "6.2", "date": "2023-06-01" }, { "version": "6.3", "date": "2023-09-11" }, { "version": "6.4", "date": "2024-01-23" }, { "version": "6.5", "date": "2025-01-18" }, { "version": "6.6", "date": "2025-02-22" }, { "version": "6.7", "date": "2026-03-31" } ], "_exports": [ "centre", "CoDa_BayesNW", "CoDa_FPCA", "diff.fts", "dynamic_FLR", "dynupdate", "ER_GR", "error", "extract", "facf", "farforecast", "fbootstrap", "forecast.ftsm", "forecastfplsr", "fplsr", "ftsm", "ftsmiterativeforecasts", "ftsmweightselect", "GAEVforecast", "H_estimate_RS", "Horta_Ziegelmann_FPCA", "is.fts", "isfe.fts", "long_run_covariance_estimation", "LQDT_FPCA", "MAF_multivariate", "mean.fts", "median.fts", "MFDM", "pcscorebootstrapdata", "plot.fm", "plot.fmres", "plot.ftsf", "plot.ftsm", "plotfplsr", "quantile", "quantile.fts", "residuals.fm", "sd", "sd.default", "sd.fts", "sim_FARMA", "skew_t_fun", "stop_time_detect", "stop_time_sim_data", "summary.fm", "T_stationary", "var", "var.default", "var.fts" ], "_datasets": [ { "name": "DJI_return", "title": "Dow Jones Industrial Average (DJIA)", "object": "DJI_return", "class": [ "matrix", "array" ], "fields": [ "Ret1", "Ret2", "Ret3", "Ret4", "Ret5", "Ret6", "Ret7", "Ret8", "Ret9", "Ret10", "Ret11", "Ret12", "Ret13", "Ret14", "Ret15", "Ret16", "Ret17", "Ret18", "Ret19", "Ret20", "Ret21", "Ret22", "Ret23", "Ret24", "Ret25", "Ret26", "Ret27", "Ret28", "Ret29", "Ret30" ], "rows": 165, "table": true, "tojson": true }, { "name": "pm_10_GR", "title": "Particulate Matter Concentrations (pm10)", "object": "pm_10_GR", "class": [ "sfts", "fts", "fds" ], "fields": [], "table": false, "tojson": false }, { "name": "pm_10_GR_sqrt", "title": "Particulate Matter Concentrations (pm10)", "object": "pm_10_GR_sqrt", "class": [ "sfts", "fts", "fds" ], "fields": [], "table": false, "tojson": false } ], "_help": [ { "page": "ftsa-package", "title": "Functional Time Series Analysis", "topics": [ "ftsa-package", "ftsa" ] }, { "page": "centre", "title": "Mean function, variance function, median function, trim mean function of functional data", "topics": [ "centre" ] }, { "page": "CoDa_BayesNW", "title": "Compositional data analytic approach and nonparametric function-on-function regression for forecasting density", "topics": [ "CoDa_BayesNW" ] }, { "page": "CoDa_FPCA", "title": "Compositional data analytic approach and functional principal component analysis for forecasting density", "topics": [ "CoDa_FPCA" ] }, { "page": "diff.fts", "title": "Differences of a functional time series", "topics": [ "diff.fts" ] }, { "page": "DJI_return", "title": "Dow Jones Industrial Average (DJIA)", "topics": [ "DJI_return" ] }, { "page": "dynamic_FLR", "title": "Dynamic updates via functional linear regression", "topics": [ "dynamic_FLR" ] }, { "page": "dynupdate", "title": "Dynamic updates via BM, OLS, RR and PLS methods", "topics": [ "dynupdate" ] }, { "page": "ER_GR", "title": "Selection of the number of principal components", "topics": [ "ER_GR" ] }, { "page": "error", "title": "Forecast error measure", "topics": [ "error" ] }, { "page": "extract", "title": "Extract variables or observations", "topics": [ "extract" ] }, { "page": "facf", "title": "Functional autocorrelation function", "topics": [ "facf" ] }, { "page": "farforecast", "title": "Functional data forecasting through functional principal component autoregression", "topics": [ "farforecast" ] }, { "page": "fbootstrap", "title": "Bootstrap independent and identically distributed functional data", "topics": [ "fbootstrap" ] }, { "page": "forecast.ftsm", "title": "Forecast functional time series", "topics": [ "forecast.ftsm" ] }, { "page": "forecastfplsr", "title": "Forecast functional time series", "topics": [ "forecastfplsr" ] }, { "page": "fplsr", "title": "Functional partial least squares regression", "topics": [ "fplsr" ] }, { "page": "ftsm", "title": "Fit functional time series model", "topics": [ "ftsm" ] }, { "page": "ftsmiterativeforecasts", "title": "Forecast functional time series", "topics": [ "ftsmiterativeforecasts" ] }, { "page": "ftsmweightselect", "title": "Selection of the weight parameter used in the weighted functional time series model.", "topics": [ "ftsmweightselect" ] }, { "page": "GAEVforecast", "title": "Fit a generalized additive extreme value model to the functional data with given basis numbers", "topics": [ "GAEVforecast" ] }, { "page": "H_estimate_RS", "title": "Estimation of long-memory parameter", "topics": [ "H_estimate_RS" ] }, { "page": "Horta_Ziegelmann_FPCA", "title": "Dynamic functional principal component analysis for density forecasting", "topics": [ "Horta_Ziegelmann_FPCA" ] }, { "page": "is.fts", "title": "Test for functional time series", "topics": [ "is.fts" ] }, { "page": "isfe.fts", "title": "Integrated Squared Forecast Error for models of various orders", "topics": [ "isfe.fts" ] }, { "page": "long_run_covariance_estimation", "title": "Estimating long-run covariance function for a functional time series", "topics": [ "long_run_covariance_estimation" ] }, { "page": "LQDT_FPCA", "title": "Log quantile density transform", "topics": [ "LQDT_FPCA" ] }, { "page": "MAF_multivariate", "title": "Maximum autocorrelation factors", "topics": [ "MAF_multivariate" ] }, { "page": "mean.fts", "title": "Mean functions for functional time series", "topics": [ "mean.fts" ] }, { "page": "median.fts", "title": "Median functions for functional time series", "topics": [ "median.fts" ] }, { "page": "MFDM", "title": "Multilevel functional data method", "topics": [ "MFDM" ] }, { "page": "pcscorebootstrapdata", "title": "Bootstrap independent and identically distributed functional data or functional time series", "topics": [ "pcscorebootstrapdata" ] }, { "page": "plot.fm", "title": "Plot fitted model components for a functional model", "topics": [ "plot.fm" ] }, { "page": "plot.fmres", "title": "Plot residuals from a fitted functional model.", "topics": [ "plot.fmres" ] }, { "page": "plot.ftsf", "title": "Plot fitted model components for a functional time series model", "topics": [ "plot.ftsf" ] }, { "page": "plot.ftsm", "title": "Plot fitted model components for a functional time series model", "topics": [ "plot.ftsm" ] }, { "page": "plotfplsr", "title": "Plot fitted model components for a functional time series model", "topics": [ "plotfplsr" ] }, { "page": "pm_10_GR", "title": "Particulate Matter Concentrations (pm10)", "topics": [ "pm_10_GR", "pm_10_GR_sqrt" ] }, { "page": "quantile", "title": "Quantile", "topics": [ "quantile" ] }, { "page": "quantile.fts", "title": "Quantile functions for functional time series", "topics": [ "quantile.fts" ] }, { "page": "residuals.fm", "title": "Compute residuals from a functional model", "topics": [ "residuals.fm" ] }, { "page": "sd", "title": "Standard deviation", "topics": [ "sd", "sd.default" ] }, { "page": "sd.fts", "title": "Standard deviation functions for functional time series", "topics": [ "sd.fts" ] }, { "page": "sim_FARMA", "title": "Simulating data from a functional autoregressive moving average process", "topics": [ "sim_FARMA" ] }, { "page": "skew_t_fun", "title": "Skewed t distribution", "topics": [ "skew_t_fun" ] }, { "page": "stop_time_detect", "title": "Detection of the optimal stopping time in a curve time series", "topics": [ "stop_time_detect" ] }, { "page": "stop_time_sim_data", "title": "Simulated functional time series from a functional autoregression of order one", "topics": [ "stop_time_sim_data" ] }, { "page": "summary.fm", "title": "Summary for functional time series model", "topics": [ "summary.fm" ] }, { "page": "T_stationary", "title": "Testing stationarity of functional time series", "topics": [ "T_stationary" ] }, { "page": "var", "title": "Variance", "topics": [ "var", "var.default" ] }, { "page": "var.fts", "title": "Variance functions for functional time series", "topics": [ "var.fts" ] } ], "_rundeps": [ "abind", "ash", "backports", "base64enc", "bitops", "boot", "bslib", "cachem", "checkmate", "class", "cli", "cluster", "colorspace", "cpp11", "cvar", "data.table", "deSolve", "digest", "e1071", "ecp", "evaluate", "evgam", "farver", "fastICA", "fastmap", "fBasics", "fda", "fdapace", "fds", "fGarch", "FNN", "fontawesome", "forecast", "foreign", "Formula", "fracdiff", "fs", "gbutils", "generics", "geometry", "ggplot2", "glue", "GPArotation", "gridExtra", "gss", "gtable", "hdrcde", "highr", "Hmisc", "htmlTable", "htmltools", "htmlwidgets", "isoband", "jquerylib", "jsonlite", "kernlab", "KernSmooth", "knitr", "ks", "labeling", "LaplacesDemon", "lattice", "lifecycle", "linprog", "Lmoments", "lmtest", "locfit", "lpSolve", "magic", "magrittr", "MASS", "Matrix", "mclust", "memoise", "mgcv", "mime", "mnormt", "multicool", "mvtnorm", "nlme", "nnet", "numDeriv", "pcaPP", "pdfCluster", "pracma", "proxy", "psych", "R6", "rainbow", "rappdirs", "rbibutils", "RColorBrewer", "Rcpp", "RcppArmadillo", "RcppEigen", "RcppProgress", "RCurl", "Rdpack", "rlang", "rmarkdown", "ROOPSD", "rpart", "rstudioapi", "S7", "sandwich", "sass", "scales", "sde", "spatial", "stabledist", "stringi", "stringr", "strucchange", "timeDate", "timeSeries", "tinytex", "urca", "vars", "vctrs", "viridisLite", "withr", "xfun", "yaml", "zoo" ], "_score": 5.026206951263732, "_indexed": true, "_nocasepkg": "ftsa", "_universes": [ "cran" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "6.7", "date": "2026-05-26T06:06:35.000Z", "distro": "noble", "commit": "ff39696f94dd5f9067e188712ba59b63f1ee40c3", "fileid": "caebc3c0635ef50f5a775e54c417183759f1280c3e5ef4c98c105b84292b456f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/26435082509" }, { "r": "4.6.0", "os": "linux", "version": "6.7", "date": "2026-05-26T06:06:38.000Z", "distro": "noble", "commit": "ff39696f94dd5f9067e188712ba59b63f1ee40c3", "fileid": "8ce7318bcb22dd7b46cb097d0480eba07508685435ab581e41077308442a5a98", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cran/actions/runs/26435082509" }, { "r": "4.6.0", "os": "wasm", "version": "6.7", "date": "2026-05-26T06:06:53.000Z", "commit": "ff39696f94dd5f9067e188712ba59b63f1ee40c3", "fileid": "9e648ae6886dc725195ee0938758da612a9c8382b5b5f3e001e0c04633523afb", "status": "success", "buildurl": "https://github.com/r-universe/cran/actions/runs/26435082509" } ] }