{ "_id": "6a10b1e8acfb0bcc41cc3f58", "Package": "tspredit", "Title": "Time Series Prediction with Integrated Tuning", "Version": "2.0.707", "Authors@R": "c( person(given = \"Eduardo\", family = \"Ogasawara\", role = c(\"aut\", \"ths\", \"cre\"),\nemail = \"eogasawara@ieee.org\", comment = c(ORCID = \"0000-0002-0466-0626\")),\nperson(given = \"Cristiane\", family = \"Gea\", role = \"aut\", email = \"cristiane.gea@eic.cefet-rj.br\"),\nperson(given = \"Diego\", family = \"Carvalho\", role = \"ctb\", email = \"diego.carvalho@cefet-rj.br\"),\nperson(given = \"Diogo\", family = \"Santos\", role = \"aut\", email = \"diogo.santos@eic.cefet-rj.br\"),\nperson(given = \"Arthur\", family = \"Garcia\", role = \"aut\", email = \"arthur.garcia@eic.cefet-rj.br\"),\nperson(given = \"Eduardo\", family = \"Bezerra\", role = \"ctb\", email = \"ebezerra@cefet-rj.br\"),\nperson(given = \"Esther\", family = \"Pacitti\", role = \"ctb\", email = \"Esther.Pacitti@lirmm.fr\"),\nperson(given = \"Fabio\", family = \"Porto\", role = \"ctb\", email = \"fporto@lncc.br\"),\nperson(given = \"Fernando\", family = \"Alexandrino\", role = \"aut\", email = \"fernando.alexandrino@ifsp.edu.br\"),\nperson(given = \"Rebecca\", family = \"Salles\", role = \"aut\", email = \"rebecca.salles@eic.cefet-rj.br\"),\nperson(given = \"Vitoria\", family = \"Birindiba\", role = \"aut\", email = \"vitoria.birindiba@eic.cefet-rj.br\"),\nperson(given = \"CEFET/RJ\", role = \"cph\")\n)", "Description": "Time series prediction is a critical task in data\nanalysis, requiring not only the selection of appropriate\nmodels, but also suitable data preprocessing and tuning\nstrategies. TSPredIT (Time Series Prediction with Integrated\nTuning) is a framework that provides a seamless integration of\ndata preprocessing, decomposition, model training,\nhyperparameter optimization, and evaluation. Unlike other\nframeworks, TSPredIT emphasizes the co-optimization of both\npreprocessing and modeling steps, improving predictive\nperformance. It supports a variety of statistical and machine\nlearning models, filtering techniques, outlier detection, data\naugmentation, and ensemble strategies. More information is\navailable in Salles et al. .", "License": "MIT + file LICENSE", "URL": "https://cefet-rj-dal.github.io/tspredit/,\nhttps://github.com/cefet-rj-dal/tspredit", "BugReports": "https://github.com/cefet-rj-dal/tspredit/issues", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "Config/roxygen2/version": "8.0.0", "RoxygenNote": "8.0.0", "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev libssl-dev\nlibx11-dev zlib1g-dev", "Repository": "https://cefet-rj-dal.r-universe.dev", "Date/Publication": "2026-05-22 16:29:23 UTC", "RemoteUrl": "https://github.com/cefet-rj-dal/tspredit", "RemoteRef": "HEAD", "RemoteSha": "83874f341eb19efc3888d6c740c62a58e09d3e6c", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-22 19:09:04 UTC", "User": "root" }, "Author": "Eduardo Ogasawara [aut, ths, cre] (ORCID:\n),\nCristiane Gea [aut],\nDiego Carvalho [ctb],\nDiogo Santos [aut],\nArthur Garcia [aut],\nEduardo Bezerra [ctb],\nEsther Pacitti [ctb],\nFabio Porto [ctb],\nFernando Alexandrino [aut],\nRebecca Salles [aut],\nVitoria Birindiba [aut],\nCEFET/RJ [cph]", "Maintainer": "Eduardo Ogasawara ", "MD5sum": "0e96ff38acf7be1e296e4ac7254fd254", "_user": "cefet-rj-dal", "_type": "src", "_file": "tspredit_2.0.707.tar.gz", "_fileid": "f10d728bb90a4131f26037cc3bb22c8f5818caa28b5c567cf7b12ffcb51d4881", "_filesize": 539812, "_sha256": "f10d728bb90a4131f26037cc3bb22c8f5818caa28b5c567cf7b12ffcb51d4881", "_created": "2026-05-22T19:09:04.000Z", "_published": "2026-05-22T19:43:36.206Z", "_distro": "noble", "_jobs": [ { "job": 77445950137, "time": 222, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7168448296" }, { "job": 77445950072, "time": 217, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7168446748" }, { "job": 77445950154, "time": 145, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7168956552" }, { "job": 77445950194, "time": 160, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7168857018" }, { "job": 77445297306, "time": 256, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7168380035" }, { "job": 77445950149, "time": 126, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7168420086" }, { "job": 77445950229, "time": 166, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7168432143" }, { "job": 77445950173, "time": 162, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7168430794" }, { "job": 77445950184, "time": 173, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7168434982" } ], "_buildurl": "https://github.com/r-universe/cefet-rj-dal/actions/runs/26306565932", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cefet-rj-dal/tspredit", "_commit": { "id": "83874f341eb19efc3888d6c740c62a58e09d3e6c", "author": "eogasawara@ieee.org ", "committer": "eogasawara@ieee.org ", "message": "update documentation\n", "time": 1779467363 }, "_maintainer": { "name": "Eduardo Ogasawara", "email": "eogasawara@ieee.org", "login": "eogasawara", "orcid": "0000-0002-0466-0626", "description": "", "uuid": 12518421 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.1.0", "role": "Depends" }, { "package": "stats", "role": "Imports" }, { "package": "DescTools", "role": "Imports" }, { "package": "e1071", "role": "Imports" }, { "package": "elmNNRcpp", "role": "Imports" }, { "package": "FNN", "role": "Imports" }, { "package": "forecast", "role": "Imports" }, { "package": "hht", "role": "Imports" }, { "package": "KFAS", "role": "Imports" }, { "package": "mFilter", "role": "Imports" }, { "package": "nnet", "role": "Imports" }, { "package": "randomForest", "role": "Imports" }, { "package": "wavelets", "role": "Imports" }, { "package": "dplyr", "role": "Imports" }, { "package": "daltoolbox", "role": "Imports" } ], "_owner": "cefet-rj-dal", "_selfowned": true, "_usedby": 2, "_updates": [ { "week": "2026-20", "n": 1 }, { "week": "2026-21", "n": 32 } ], "_tags": [], "_stars": 10, "_contributors": [ { "user": "eogasawara", "count": 34, "uuid": 12518421 } ], "_userbio": { "uuid": 69363093, "type": "organization", "name": "Data Analytics Lab" }, "_downloads": { "count": 8605, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/tspredit" }, "_devurl": "https://github.com/cefet-rj-dal/tspredit", "_searchresults": 612, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/readme.html", "extra/readme.md", "extra/tspredit.html", "manual.pdf" ], "_homeurl": "https://github.com/cefet-rj-dal/tspredit", "_realowner": "cefet-rj-dal", "_cranurl": true, "_releases": [ { "version": "1.0.707", "date": "2023-07-19" }, { "version": "1.0.727", "date": "2023-11-02" }, { "version": "1.0.737", "date": "2023-11-09" }, { "version": "1.0.747", "date": "2023-12-22" }, { "version": "1.0.767", "date": "2024-03-26" }, { "version": "1.0.777", "date": "2024-07-29" }, { "version": "1.0.787", "date": "2024-12-04" }, { "version": "1.1.707", "date": "2025-04-24" }, { "version": "1.2.707", "date": "2025-05-13" }, { "version": "1.2.727", "date": "2025-06-22" }, { "version": "1.2.737", "date": "2025-08-20" }, { "version": "1.2.747", "date": "2025-10-27" }, { "version": "1.2.767", "date": "2026-02-16" }, { "version": "1.3.707", "date": "2026-05-14" }, { "version": "2.0.707", "date": "2026-05-22" } ], "_exports": [ "adjust_ts_data", "adjust_ts_data_mv", "do_fit", "do_predict", "loadfulldata", "MSE.ts", "plot_ts_pred_mv", "R2.ts", "sMAPE.ts", "ts_arima", "ts_arimax", "ts_aug_awareness", "ts_aug_awaresmooth", "ts_aug_flip", "ts_aug_jitter", "ts_aug_none", "ts_aug_shrink", "ts_aug_stretch", "ts_aug_wormhole", "ts_darima", "ts_data", "ts_data_mv", "ts_deterministic", "ts_elm", "ts_fil_ema", "ts_fil_emd", "ts_fil_fft", "ts_fil_hp", "ts_fil_kalman", "ts_fil_lowess", "ts_fil_ma", "ts_fil_none", "ts_fil_qes", "ts_fil_recursive", "ts_fil_remd", "ts_fil_seas_adj", "ts_fil_ses", "ts_fil_smooth", "ts_fil_spline", "ts_fil_wavelet", "ts_fil_winsor", "ts_head", "ts_integtune", "ts_knn", "ts_lagmap", "ts_lm_mv", "ts_mlp", "ts_mv_spec", "ts_norm_an", "ts_norm_diff", "ts_norm_gminmax", "ts_norm_none", "ts_norm_swminmax", "ts_periodic", "ts_persist", "ts_projection", "ts_reg", "ts_reg_mv", "ts_regsw", "ts_regsw_mv", "ts_rf", "ts_sample", "ts_svm", "ts_tune", "ts_var", "ts_warma", "tsanutils", "tslagutils" ], "_datasets": [ { "name": "bioenergy", "title": "FAOSTAT Bioenergy Database", "object": "bioenergy", "file": "bioenergy.RData", "class": [ "list" ], "fields": [], "table": true, "tojson": true }, { "name": "CATS", "title": "CATS Time Series Competition", "object": "CATS", "file": "CATS.RData", "class": [ "data.frame" ], "fields": [ "V1", "V2", "V3", "V4", "V5", "split" ], "rows": 30, "table": true, "tojson": true }, { "name": "climate", "title": "FAOSTAT Temperature Change on Land", "object": "climate", "file": "climate.RData", "class": [ "list" ], "fields": [], "table": true, "tojson": true }, { "name": "emissions", "title": "FAOSTAT Emissions Totals", "object": "emissions", "file": "emissions.RData", "class": [ "list" ], "fields": [], "table": true, "tojson": true }, { "name": "EUNITE.Loads", "title": "EUNITE Competition – Half-Hourly Electrical Loads", "object": "EUNITE.Loads", "file": "EUNITE.Loads.RData", "class": [ "data.frame" ], "fields": [ "X00.30", "X01.00", "X01.30", "X02.00", "X02.30", "X03.00", "X03.30", "X04.00", "X04.30", "X05.00", "X05.30", "X06.00", "X06.30", "X07.00", "X07.30", "X08.00", "X08.30", "X09.00", "X09.30", "X10.00", "X10.30", "X11.00", "X11.30", "X12.00", "X12.30", "X13.00", "X13.30", "X14.00", "X14.30", "X15.00", "X15.30", "X16.00", "X16.30", "X17.00", "X17.30", "X18.00", "X18.30", "X19.00", "X19.30", "X20.00", "X20.30", "X21.00", "X21.30", "X22.00", "X22.30", "X23.00", "X23.30", "X24.00", "split" ], "rows": 30, "table": true, "tojson": true }, { "name": "EUNITE.Reg", "title": "EUNITE Competition – Regressors for Load Forecasting", "object": "EUNITE.Reg", "file": "EUNITE.Reg.RData", "class": [ "data.frame" ], "fields": [ "Holiday", "Weekday", "split" ], "rows": 30, "table": true, "tojson": true }, { "name": "EUNITE.Temp", "title": "EUNITE Competition – Average Daily Temperatures", "object": "EUNITE.Temp", "file": "EUNITE.Temp.RData", "class": [ "data.frame" ], "fields": [ "Temperature", "split" ], "rows": 30, "table": true, "tojson": true }, { "name": "fertilizers", "title": "FAOSTAT Fertilizers by Nutrient", "object": "fertilizers", "file": "fertilizers.RData", "class": [ "list" ], "fields": [], "table": true, "tojson": true }, { "name": "gdp", "title": "Gross Domestic Product and Agriculture Value Added", "object": "gdp", "file": "gdp.RData", "class": [ "list" ], "fields": [], "table": true, "tojson": true }, { "name": "ipeadata.d", "title": "Ipea Daily Macroeconomic Dataset", "object": "ipeadata.d", "file": "ipeadata.d.RData", "class": [ "data.frame" ], "fields": [ "GM366_IBVSP366", "GM366_ERC366", "GM366_EREURO366", "GM366_ERPV366", "GM366_ERV366", "GM366_TJOVER366", "GM366_TJTR366", "SECEX366_MVTOT366", "SECEX366_XVTOT366", "JPM366_EMBI366", "BM366_TJOVER366", "GM366_TJOVERV366", "split" ], "rows": 30, "table": true, "tojson": true }, { "name": "ipeadata.m", "title": "Ipea Monthly Macroeconomic Dataset", "object": "ipeadata.m", "file": "ipeadata.m.RData", "class": [ "data.frame" ], "fields": [ "BM12_ERC12", "BM12_ERV12", "IGP12_IGPDI12", "FUNCEX12_MDPT12", "FUNCEX12_XPT12", "PRECOS12_INPC12", "PRECOS12_INPCBR12", "PRECOS12_IPCA12", "SEADE12_TDAGSP12", "SEADE12_TDOTSP12", "SEADE12_TDOPSP12", "GAC12_SALMINRE12", "IGP12_IGPM12", "PRECOS12_IPCAG12", "IGP12_IGPDIG12", "IGP12_IGPMG12", "IGP12_IGPOGG12", "PRECOS12_IPCA15G12", "BM12_PIB12", "MTE12_SALMIN12", "BM12_TJOVER12", "SEADE12_TDTGSP12", "PMEN12_TD12", "split" ], "rows": 30, "table": true, "tojson": true }, { "name": "m1", "title": "M1 Competition Time Series", "object": "m1", "file": "m1.RData", "class": [ "list" ], "fields": [], "table": true, "tojson": true }, { "name": "m3", "title": "M3 Competition Time Series", "object": "m3", "file": "m3.RData", "class": [ "list" ], "fields": [], "table": true, "tojson": true }, { "name": "m4", "title": "M4 Competition Time Series", "object": "m4", "file": "m4.RData", "class": [ "list" ], "fields": [], "table": true, "tojson": true }, { "name": "NN3", "title": "NN3 Time Series Competition - Dataset A", "object": "NN3", "file": "NN3.RData", "class": [ "data.frame" ], "fields": [ "NN3.001", "NN3.002", "NN3.003", "NN3.004", "NN3.005", "NN3.006", "NN3.007", "NN3.008", "NN3.009", "NN3.010", "NN3.011", "NN3.012", "NN3.013", "NN3.014", "NN3.015", "NN3.016", "NN3.017", "NN3.018", "NN3.019", "NN3.020", "NN3.021", "NN3.022", "NN3.023", "NN3.024", "NN3.025", "NN3.026", "NN3.027", "NN3.028", "NN3.029", "NN3.030", "NN3.031", "NN3.032", "NN3.033", "NN3.034", "NN3.035", "NN3.036", "NN3.037", "NN3.038", "NN3.039", "NN3.040", "NN3.041", "NN3.042", "NN3.043", "NN3.044", "NN3.045", "NN3.046", "NN3.047", "NN3.048", "NN3.049", "NN3.050", "NN3.051", "NN3.052", "NN3.053", "NN3.054", "NN3.055", "NN3.056", "NN3.057", "NN3.058", "NN3.059", "NN3.060", "NN3.061", "NN3.062", "NN3.063", "NN3.064", "NN3.065", "NN3.066", "NN3.067", "NN3.068", "NN3.069", "NN3.070", "NN3.071", "NN3.072", "NN3.073", "NN3.074", "NN3.075", "NN3.076", "NN3.077", "NN3.078", "NN3.079", "NN3.080", "NN3.081", "NN3.082", "NN3.083", "NN3.084", "NN3.085", "NN3.086", "NN3.087", "NN3.088", "NN3.089", "NN3.090", "NN3.091", "NN3.092", "NN3.093", "NN3.094", "NN3.095", "NN3.096", "NN3.097", "NN3.098", "NN3.099", "NN3.100", "NN3_101", "NN3_102", "NN3_103", "NN3_104", "NN3_105", "NN3_106", "NN3_107", "NN3_108", "NN3_109", "NN3_110", "NN3_111", "split" ], "rows": 30, "table": true, "tojson": true }, { "name": "NN5", "title": "NN5 Time Series Competition", "object": "NN5", "file": "NN5.RData", "class": [ "data.frame" ], "fields": [ "NN5.001", "NN5.002", "NN5.003", "NN5.004", "NN5.005", "NN5.006", "NN5.007", "NN5.008", "NN5.009", "NN5.010", "NN5.011", "NN5.012", "NN5.013", "NN5.014", "NN5.015", "NN5.016", "NN5.017", "NN5.018", "NN5.019", "NN5.020", "NN5.021", "NN5.022", "NN5.023", "NN5.024", "NN5.025", "NN5.026", "NN5.027", "NN5.028", "NN5.029", "NN5.030", "NN5.031", "NN5.032", "NN5.033", "NN5.034", "NN5.035", "NN5.036", "NN5.037", "NN5.038", "NN5.039", "NN5.040", "NN5.041", "NN5.042", "NN5.043", "NN5.044", "NN5.045", "NN5.046", "NN5.047", "NN5.048", "NN5.049", "NN5.050", "NN5.051", "NN5.052", "NN5.053", "NN5.054", "NN5.055", "NN5.056", "NN5.057", "NN5.058", "NN5.059", "NN5.060", "NN5.061", "NN5.062", "NN5.063", "NN5.064", "NN5.065", "NN5.066", "NN5.067", "NN5.068", "NN5.069", "NN5.070", "NN5.071", "NN5.072", "NN5.073", "NN5.074", "NN5.075", "NN5.076", "NN5.077", "NN5.078", "NN5.079", "NN5.080", "NN5.081", "NN5.082", "NN5.083", "NN5.084", "NN5.085", "NN5.086", "NN5.087", "NN5.088", "NN5.089", "NN5.090", "NN5.091", "NN5.092", "NN5.093", "NN5.094", "NN5.095", "NN5.096", "NN5.097", "NN5.098", "NN5.099", "NN5.100", "NN5.101", "NN5.102", "NN5.103", "NN5.104", "NN5.105", "NN5.106", "NN5.107", "NN5.108", "NN5.109", "NN5.110", "NN5.111", "split" ], "rows": 30, "table": true, "tojson": true }, { "name": "pesticides", "title": "Pesticides Use Statistics", "object": "pesticides", "file": "pesticides.RData", "class": [ "list" ], "fields": [], "table": true, "tojson": true }, { "name": "SantaFe.A", "title": "Santa Fe Time Series Competition - Series A", "object": "SantaFe.A", "file": "SantaFe.A.RData", "class": [ "data.frame" ], "fields": [ "V1", "split" ], "rows": 30, "table": true, "tojson": true }, { "name": "SantaFe.D", "title": "Santa Fe Time Series Competition - Series D", "object": "SantaFe.D", "file": "SantaFe.D.RData", "class": [ "data.frame" ], "fields": [ "V1", "split" ], "rows": 30, "table": true, "tojson": true }, { "name": "stocks", "title": "IBOVESPA's 50 Most Traded Stocks", "object": "stocks", "file": "stocks.RData", "class": [ "list" ], "fields": [], "table": true, "tojson": true }, { "name": "tsd", "title": "Time series for forecasting examples", "object": "tsd", "file": "tsd.RData", "class": [ "data.frame" ], "fields": [ "x", "y" ], "rows": 41, "table": true, "tojson": true } ], "_help": [ { "page": "sub-.ts_data", "title": "Subset Extraction for Time Series Data", "topics": [ "[.ts_data" ] }, { "page": "adjust_ts_data", "title": "Adjust 'ts_data'", "topics": [ "adjust_ts_data" ] }, { "page": "adjust_ts_data_mv", "title": "Adjust 'ts_data_mv'", "topics": [ "adjust_ts_data_mv" ] }, { "page": "bioenergy", "title": "FAOSTAT Bioenergy Database", "topics": [ "bioenergy" ] }, { "page": "CATS", "title": "CATS Time Series Competition", "topics": [ "CATS" ] }, { "page": "climate", "title": "FAOSTAT Temperature Change on Land", "topics": [ "climate" ] }, { "page": "do_fit", "title": "Fit Time Series Model", "topics": [ "do_fit" ] }, { "page": "do_predict", "title": "Predict Time Series Model", "topics": [ "do_predict" ] }, { "page": "emissions", "title": "FAOSTAT Emissions Totals", "topics": [ "emissions" ] }, { "page": "EUNITE.Loads", "title": "EUNITE Competition – Half-Hourly Electrical Loads", "topics": [ "EUNITE.Loads" ] }, { "page": "EUNITE.Reg", "title": "EUNITE Competition – Regressors for Load Forecasting", "topics": [ "EUNITE.Reg" ] }, { "page": "EUNITE.Temp", "title": "EUNITE Competition – Average Daily Temperatures", "topics": [ "EUNITE.Temp" ] }, { "page": "fertilizers", "title": "FAOSTAT Fertilizers by Nutrient", "topics": [ "fertilizers" ] }, { "page": "gdp", "title": "Gross Domestic Product and Agriculture Value Added", "topics": [ "gdp" ] }, { "page": "ipeadata.d", "title": "Ipea Daily Macroeconomic Dataset", "topics": [ "ipeadata.d" ] }, { "page": "ipeadata.m", "title": "Ipea Monthly Macroeconomic Dataset", "topics": [ "ipeadata.m" ] }, { "page": "loadfulldata", "title": "Load Full Dataset From Mini Data Object", "topics": [ "loadfulldata" ] }, { "page": "m1", "title": "M1 Competition Time Series", "topics": [ "m1" ] }, { "page": "m3", "title": "M3 Competition Time Series", "topics": [ "m3" ] }, { "page": "m4", "title": "M4 Competition Time Series", "topics": [ "m4" ] }, { "page": "MSE.ts", "title": "MSE", "topics": [ "MSE.ts" ] }, { "page": "NN3", "title": "NN3 Time Series Competition - Dataset A", "topics": [ "NN3" ] }, { "page": "NN5", "title": "NN5 Time Series Competition", "topics": [ "NN5" ] }, { "page": "pesticides", "title": "Pesticides Use Statistics", "topics": [ "pesticides" ] }, { "page": "plot_ts_pred_mv", "title": "Plot Multivariate Forecast Paths", "topics": [ "plot_ts_pred_mv" ] }, { "page": "R2.ts", "title": "R2", "topics": [ "R2.ts" ] }, { "page": "SantaFe.A", "title": "Santa Fe Time Series Competition - Series A", "topics": [ "SantaFe.A" ] }, { "page": "SantaFe.D", "title": "Santa Fe Time Series Competition - Series D", "topics": [ "SantaFe.D" ] }, { "page": "select_hyper.ts_tune", "title": "Select Optimal Hyperparameters for Time Series Models", "topics": [ "select_hyper.ts_tune" ] }, { "page": "sMAPE.ts", "title": "sMAPE", "topics": [ "sMAPE.ts" ] }, { "page": "stocks", "title": "IBOVESPA's 50 Most Traded Stocks", "topics": [ "stocks" ] }, { "page": "ts_arima", "title": "ARIMA", "topics": [ "ts_arima" ] }, { "page": "ts_arimax", "title": "ARIMAX", "topics": [ "ts_arimax" ] }, { "page": "ts_aug_awareness", "title": "Augmentation by Awareness", "topics": [ "ts_aug_awareness" ] }, { "page": "ts_aug_awaresmooth", "title": "Augmentation by Awareness Smooth", "topics": [ "ts_aug_awaresmooth" ] }, { "page": "ts_aug_flip", "title": "Augmentation by Flip", "topics": [ "ts_aug_flip" ] }, { "page": "ts_aug_jitter", "title": "Augmentation by Jitter", "topics": [ "ts_aug_jitter" ] }, { "page": "ts_aug_none", "title": "No Augmentation", "topics": [ "ts_aug_none" ] }, { "page": "ts_aug_shrink", "title": "Augmentation by Shrink", "topics": [ "ts_aug_shrink" ] }, { "page": "ts_aug_stretch", "title": "Augmentation by Stretch", "topics": [ "ts_aug_stretch" ] }, { "page": "ts_aug_wormhole", "title": "Augmentation by Wormhole", "topics": [ "ts_aug_wormhole" ] }, { "page": "ts_darima", "title": "DARIMA", "topics": [ "ts_darima" ] }, { "page": "ts_data", "title": "ts_data", "topics": [ "ts_data" ] }, { "page": "ts_data_mv", "title": "Multivariate Time Series Data", "topics": [ "ts_data_mv" ] }, { "page": "ts_deterministic", "title": "Deterministic Univariate Predictor", "topics": [ "ts_deterministic" ] }, { "page": "ts_elm", "title": "ELM", "topics": [ "ts_elm" ] }, { "page": "ts_fil_ema", "title": "Exponential Moving Average (EMA)", "topics": [ "ts_fil_ema" ] }, { "page": "ts_fil_emd", "title": "EMD Filter", "topics": [ "ts_fil_emd" ] }, { "page": "ts_fil_fft", "title": "FFT Filter", "topics": [ "ts_fil_fft" ] }, { "page": "ts_fil_hp", "title": "Hodrick-Prescott Filter", "topics": [ "ts_fil_hp" ] }, { "page": "ts_fil_kalman", "title": "Kalman Filter", "topics": [ "ts_fil_kalman" ] }, { "page": "ts_fil_lowess", "title": "LOWESS Smoothing", "topics": [ "ts_fil_lowess" ] }, { "page": "ts_fil_ma", "title": "Moving Average (MA)", "topics": [ "ts_fil_ma" ] }, { "page": "ts_fil_none", "title": "No Filter", "topics": [ "ts_fil_none" ] }, { "page": "ts_fil_qes", "title": "Quadratic Exponential Smoothing", "topics": [ "ts_fil_qes" ] }, { "page": "ts_fil_recursive", "title": "Recursive Filter", "topics": [ "ts_fil_recursive" ] }, { "page": "ts_fil_remd", "title": "Robust EMD Filter", "topics": [ "ts_fil_remd" ] }, { "page": "ts_fil_seas_adj", "title": "Seasonal Adjustment", "topics": [ "ts_fil_seas_adj" ] }, { "page": "ts_fil_ses", "title": "Simple Exponential Smoothing", "topics": [ "ts_fil_ses" ] }, { "page": "ts_fil_smooth", "title": "Time Series Smooth", "topics": [ "ts_fil_smooth" ] }, { "page": "ts_fil_spline", "title": "Smoothing Splines", "topics": [ "ts_fil_spline" ] }, { "page": "ts_fil_wavelet", "title": "Wavelet Filter", "topics": [ "ts_fil_wavelet" ] }, { "page": "ts_fil_winsor", "title": "Winsorization of Time Series", "topics": [ "ts_fil_winsor" ] }, { "page": "ts_head", "title": "Extract the First Observations from a 'ts_data' Object", "topics": [ "ts_head" ] }, { "page": "ts_integtune", "title": "Time Series Integrated Tune", "topics": [ "ts_integtune" ] }, { "page": "ts_knn", "title": "KNN Time Series Prediction", "topics": [ "ts_knn" ] }, { "page": "ts_lagmap", "title": "Lag Mapping for Sliding-Window Predictors", "topics": [ "ts_lagmap" ] }, { "page": "ts_lm_mv", "title": "Multivariate Linear Regression", "topics": [ "ts_lm_mv" ] }, { "page": "ts_mlp", "title": "MLP", "topics": [ "ts_mlp" ] }, { "page": "ts_mv_spec", "title": "Multivariate Model Specification", "topics": [ "ts_mv_spec" ] }, { "page": "ts_norm_an", "title": "Adaptive Normalization", "topics": [ "ts_norm_an" ] }, { "page": "ts_norm_diff", "title": "First Differences", "topics": [ "ts_norm_diff" ] }, { "page": "ts_norm_gminmax", "title": "Global Min–Max Normalization", "topics": [ "ts_norm_gminmax" ] }, { "page": "ts_norm_none", "title": "No Normalization", "topics": [ "ts_norm_none" ] }, { "page": "ts_norm_swminmax", "title": "Sliding-Window Min–Max Normalization", "topics": [ "ts_norm_swminmax" ] }, { "page": "ts_periodic", "title": "Periodic Deterministic Predictor", "topics": [ "ts_periodic" ] }, { "page": "ts_persist", "title": "Persistence Deterministic Predictor", "topics": [ "ts_persist" ] }, { "page": "ts_projection", "title": "Time Series Projection", "topics": [ "ts_projection" ] }, { "page": "ts_reg", "title": "TSReg", "topics": [ "ts_reg" ] }, { "page": "ts_reg_mv", "title": "Target-Centered Multivariate Regression Base", "topics": [ "ts_reg_mv" ] }, { "page": "ts_regsw", "title": "TSRegSW", "topics": [ "ts_regsw" ] }, { "page": "ts_regsw_mv", "title": "Multivariate Sliding-Window Regressor", "topics": [ "ts_regsw_mv" ] }, { "page": "ts_rf", "title": "Random Forest", "topics": [ "ts_rf" ] }, { "page": "ts_sample", "title": "Time Series Sample", "topics": [ "ts_sample" ] }, { "page": "ts_svm", "title": "SVM", "topics": [ "ts_svm" ] }, { "page": "ts_tune", "title": "Time Series Tune", "topics": [ "ts_tune" ] }, { "page": "ts_var", "title": "Vector Autoregression", "topics": [ "ts_var" ] }, { "page": "ts_warma", "title": "WARMA", "topics": [ "ts_warma" ] }, { "page": "tsanutils", "title": "Adaptive Normalization Utilities", "topics": [ "tsanutils" ] }, { "page": "tsd", "title": "Time series for forecasting examples", "topics": [ "tsd" ] }, { "page": "tslagutils", "title": "Time Series Lag Utilities", "topics": [ "tslagutils" ] } ], "_readme": "https://github.com/cefet-rj-dal/tspredit/raw/HEAD/README.md", "_rundeps": [ "arules", "arulesSequences", "askpass", "bit", "bit64", "boot", "caret", "cellranger", "class", "cli", "clipr", "clock", "cluster", "codetools", "colorspace", "cpp11", "crayon", "curl", "daltoolbox", "data.table", "dbscan", "DescTools", "diagram", "digest", "dotCall64", "dplyr", "e1071", "elmNNRcpp", "EMD", "Exact", "expm", "farver", "fields", "FNN", "forcats", "foreach", "forecast", "fracdiff", "fs", "future", "future.apply", "generics", "ggplot2", "gld", "globals", "glue", "gower", "gtable", "hardhat", "haven", "hht", "hms", "httr", "ipred", "isoband", "iterators", "jsonlite", "KernelKnn", "KernSmooth", "KFAS", "labeling", "lattice", "lava", "lifecycle", "listenv", "lmom", "lmtest", "locfit", "lubridate", "magrittr", "maps", "MASS", "Matrix", "mclust", "mFilter", "mime", "ModelMetrics", "mvtnorm", "nlme", "nnet", "numDeriv", "openssl", "parallelly", "pillar", "pkgconfig", "plyr", "prettyunits", "pROC", "prodlim", "progress", "progressr", "proxy", "purrr", "R6", "randomForest", "RColorBrewer", "Rcpp", "RcppArmadillo", "readr", "readxl", "recipes", "rematch", "reshape", "reshape2", "rlang", "rootSolve", "rpart", "rstudioapi", "S7", "scales", "shape", "spam", "sparsevctrs", "SQUAREM", "stringi", "stringr", "survival", "sys", "tibble", "tidyr", "tidyselect", "timechange", "timeDate", "tree", "tzdb", "urca", "utf8", "vctrs", "viridisLite", "vroom", "wavelets", "withr", "zoo" ], "_score": 7.499653547192784, "_indexed": true, "_nocasepkg": "tspredit", "_universes": [ "cefet-rj-dal", "eogasawara" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "2.0.707", "date": "2026-05-22T19:11:50.000Z", "distro": "noble", "commit": "83874f341eb19efc3888d6c740c62a58e09d3e6c", "fileid": "0d67b68344b631588afcb7e4881c69eaf4971dd42f6a7947edc29ac2a8a03a12", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cefet-rj-dal/actions/runs/26306565932" }, { "r": "4.6.0", "os": "linux", "version": "2.0.707", "date": "2026-05-22T19:11:52.000Z", "distro": "noble", "commit": "83874f341eb19efc3888d6c740c62a58e09d3e6c", "fileid": "047e4e8568dbb1c3ec54421aedbbecd282cff5fcdc2a4e06e077539f0a69d504", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cefet-rj-dal/actions/runs/26306565932" }, { "r": "4.5.3", "os": "mac", "version": "2.0.707", "date": "2026-05-22T19:42:26.000Z", "commit": "83874f341eb19efc3888d6c740c62a58e09d3e6c", "fileid": "71de232c75c626068bba4002e87c089ba7b2e4bff7073c7f7acbfe4b7203eca0", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cefet-rj-dal/actions/runs/26306565932" }, { "r": "4.6.0", "os": "mac", "version": "2.0.707", "date": "2026-05-22T19:36:23.000Z", "commit": "83874f341eb19efc3888d6c740c62a58e09d3e6c", "fileid": "542848cf12c0e8d1bdcb7f4cde8589ec2f26ca7983d455a1e3d6b86bcd51df78", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cefet-rj-dal/actions/runs/26306565932" }, { "r": "4.6.0", "os": "wasm", "version": "2.0.707", "date": "2026-05-22T19:11:40.000Z", "commit": "83874f341eb19efc3888d6c740c62a58e09d3e6c", "fileid": "72d42b7a57a360af83f5f7abf6fe3294e908bba0eeb1a40934b452f274fd4a0d", "status": "success", "buildurl": "https://github.com/r-universe/cefet-rj-dal/actions/runs/26306565932" }, { "r": "4.7.0", "os": "win", "version": "2.0.707", "date": "2026-05-22T19:10:41.000Z", "commit": "83874f341eb19efc3888d6c740c62a58e09d3e6c", "fileid": "177eb31b3e393306be1ce46981e3ce9a0311ba1911c7e1c5ecd666ceb5c00a06", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cefet-rj-dal/actions/runs/26306565932" }, { "r": "4.5.3", "os": "win", "version": "2.0.707", "date": "2026-05-22T19:10:37.000Z", "commit": "83874f341eb19efc3888d6c740c62a58e09d3e6c", "fileid": "6d2d7a209c4189ebeb251ad88322df0e47f61d985ef9361a5476cd28ba59b363", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cefet-rj-dal/actions/runs/26306565932" }, { "r": "4.6.0", "os": "win", "version": "2.0.707", "date": "2026-05-22T19:10:54.000Z", "commit": "83874f341eb19efc3888d6c740c62a58e09d3e6c", "fileid": "26b2f4c429ef0425188e2fc0b77e540d0549460c90a47843ff1607ff051ca909", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/cefet-rj-dal/actions/runs/26306565932" } ] }