{ "_id": "6acb821ffe5cc25786e90ffd", "Package": "tscount", "Type": "Package", "Title": "Analysis of Count Time Series", "Version": "1.4.4", "Date": "2023-05-10", "Authors@R": "c(\nperson(\"Tobias\", \"Liboschik\", role=c(\"aut\", \"cre\"), email=\"liboschik@statistik.tu-dortmund.de\"),\nperson(\"Roland\", \"Fried\", role=c(\"aut\"), email=\"fried@statistik.tu-dortmund.de\"),\nperson(\"Konstantinos\", \"Fokianos\", role=c(\"aut\"), email=\"fokianos@ucy.ac.cy\"),\nperson(\"Philipp\", \"Probst\", role=c(\"aut\"), email=\"philipp.probst@tu-dortmund.de\"),\nperson(\"Jonathan\", \"Rathjens\", role=c(\"ctb\"), email=\"jonathan.rathjens@tu-dortmund.de\"),\nperson(\"Nicolò\", \"Rubattu\", role=c(\"ctb\"), email=\"nicolo.rubattu@idsia.ch\"))", "Description": "Likelihood-based methods for model fitting and assessment,\nprediction and intervention analysis of count time series\nfollowing generalized linear models are provided, see Liboschik\net al. (2017) . Models with the\nidentity and with the logarithmic link function are allowed.\nThe conditional distribution can be Poisson or Negative\nBinomial.", "License": "GPL-2 | GPL-3", "URL": "http://tscount.r-forge.r-project.org", "ByteCompile": "true", "NeedsCompilation": "no", "LazyData": "true", "Encoding": "UTF-8", "Repository": "https://r-forge.r-universe.dev", "Date/Publication": "2023-05-10 12:56:11 UTC", "RemoteUrl": "https://github.com/r-forge/tscount", "RemoteRef": "HEAD", "RemoteSha": "d4774dc5aa905ab969bf5d51faafaf51c0a3a431", "RemoteSubdir": "pkg", "Packaged": { "Date": "2026-10-11 12:30:33 UTC", "User": "root" }, "Author": "Tobias Liboschik [aut, cre],\nRoland Fried [aut],\nKonstantinos Fokianos [aut],\nPhilipp Probst [aut],\nJonathan Rathjens [ctb],\nNicolò Rubattu [ctb]", "Maintainer": "Tobias Liboschik ", "_user": "r-forge", "_type": "src", "_file": "tscount_1.4.4.tar.gz", "_fileid": "https://r2.ropensci.org/fb63cc45ed1337fad0182acf40b92f304720bc3b57f53d7fdb174e5e46c7fde3", "_filesize": 2973490, "_sha256": "fb63cc45ed1337fad0182acf40b92f304720bc3b57f53d7fdb174e5e46c7fde3", "_expires": "2027-01-19T12:33:33.000Z", "_created": "2026-10-11T12:30:33.000Z", "_published": "2026-10-11T12:33:35.260Z", "_buildurl": "https://github.com/r-universe/r-forge/actions/runs/38139303459", "_status": "success", "_host": "GitHub-Actions", "_jobs": [ { "job": 114470419175, "time": 130, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11701534066" }, { "job": 114470419209, "time": 116, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11702234541" }, { "job": 114470419249, "time": 81, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "11701464280" }, { "job": 114470419152, "time": 95, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "11701434378" }, { "job": 114469714703, "time": 219, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "11701419348" }, { "job": 114470419253, "time": 92, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "11701149956" }, { "job": 114470419237, "time": 96, "config": "windows-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11702530417" }, { "job": 114470419166, "time": 87, "config": "windows-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "11702154700" }, { "job": 114470419185, "time": 110, "config": "windows-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11701344659" } ], "_upstream": "https://github.com/r-forge/tscount", "_commit": { "id": "d4774dc5aa905ab969bf5d51faafaf51c0a3a431", "author": "nicorbtt (MSc ) ", "committer": "nicorbtt (MSc ) ", "message": "Added to the return values of the predict function the bootstrap samples used for computation of prediction intervals\n\ngit-svn-id: svn://svn.r-forge.r-project.org/svnroot/tscount@93 edb9625f-4e0d-4859-8d74-9fd3b1da38cb\n", "time": 1683723371 }, "_maintainer": { "name": "Tobias Liboschik", "email": "liboschik@statistik.tu-dortmund.de" }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "parallel", "role": "Imports" }, { "package": "ltsa", "role": "Imports" }, { "package": "Matrix", "role": "Suggests" }, { "package": "xtable", "role": "Suggests" }, { "package": "gamlss.data", "role": "Suggests" }, { "package": "surveillance", "role": "Suggests" } ], "_owner": "r-forge", "_selfowned": true, "_usedby": 1, "_updates": [], "_tags": [], "_stars": 0, "_contributors": [ { "user": "nicorbtt", "count": 1, "uuid": 61237332 }, { "user": "theussl", "count": 1, "uuid": 22165873 } ], "_userbio": { "uuid": 75573726, "type": "organization", "name": " R-Forge", "followers": 27, "description": "git-svn mirrors from R-Forge" }, "_downloads": { "count": 4616, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/tscount" }, "_mentions": 7, "_devurl": "https://github.com/r-forge/tscount", "_searchresults": 147, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/manual.pdf", "extra/NEWS.html", "extra/NEWS.txt", "extra/tscount.html" ], "_homeurl": "https://github.com/r-forge/tscount", "_realowner": "r-forge", "_cranurl": true, "_releases": [ { "version": "1.0.0", "date": "2015-02-11" }, { "version": "1.3.0", "date": "2016-05-13" }, { "version": "1.4.0", "date": "2017-09-30" }, { "version": "1.4.1", "date": "2017-11-25" }, { "version": "1.4.2", "date": "2020-03-02" }, { "version": "1.4.3", "date": "2020-09-08" } ], "_exports": [ "ardistr", "checkdistr", "ddistr", "ingarch.acf", "ingarch.mean", "ingarch.var", "interv_covariate", "interv_detect", "interv_multiple", "interv_test", "invertinfo", "marcal", "pdistr", "pit", "qdistr", "QIC", "rdistr", "scoring", "sddistr", "se", "tsglm", "tsglm.meanfit", "tsglm.sim" ], "_datasets": [ { "name": "campy", "title": "Campylobacter Infections Time Series", "object": "campy", "class": [ "ts" ], "fields": [], "table": false, "tojson": true }, { "name": "ecoli", "title": "E. coli Infections Time Series", "object": "ecoli", "class": [ "data.frame" ], "fields": [ "year", "week", "cases" ], "rows": 646, "table": true, "tojson": true }, { "name": "ehec", "title": "EHEC Infections Time Series", "object": "ehec", "class": [ "data.frame" ], "fields": [ "year", "week", "cases" ], "rows": 646, "table": true, "tojson": true }, { "name": "influenza", "title": "Influenza Infections Time Series", "object": "influenza", "class": [ "data.frame" ], "fields": [ "year", "week", "cases" ], "rows": 646, "table": true, "tojson": true }, { "name": "measles", "title": "Measles Infections Time Series", "object": "measles", "class": [ "data.frame" ], "fields": [ "year", "week", "cases" ], "rows": 646, "table": true, "tojson": true } ], "_help": [ { "page": "tscount-package", "title": "Analysis of Count Time Series", "topics": [ "tscount-package", "tscount" ] }, { "page": "campy", "title": "Campylobacter Infections Time Series", "topics": [ "campy" ] }, { "page": "countdistr", "title": "Count Data Distributions", "topics": [ "ardistr", "checkdistr", "countdistr", "ddistr", "pdistr", "qdistr", "rdistr", "sddistr" ] }, { "page": "ecoli", "title": "E. coli Infections Time Series", "topics": [ "ecoli" ] }, { "page": "ehec", "title": "EHEC Infections Time Series", "topics": [ "ehec" ] }, { "page": "influenza", "title": "Influenza Infections Time Series", "topics": [ "influenza" ] }, { "page": "ingarch.analytical", "title": "Analytical Mean, Variance and Autocorrelation of an INGARCH Process", "topics": [ "ingarch.acf", "ingarch.analytical", "ingarch.mean", "ingarch.var" ] }, { "page": "interv_covariate", "title": "Describing Intervention Effects for Time Series with Deterministic Covariates", "topics": [ "interv_covariate" ] }, { "page": "interv_detect.tsglm", "title": "Detecting an Intervention in Count Time Series Following Generalised Linear Models", "topics": [ "interv_detect", "interv_detect.tsglm" ] }, { "page": "interv_multiple.tsglm", "title": "Detecting Multiple Interventions in Count Time Series Following Generalised Linear Models", "topics": [ "interv_multiple", "interv_multiple.tsglm" ] }, { "page": "interv_test.tsglm", "title": "Testing for Interventions in Count Time Series Following Generalised Linear Models", "topics": [ "interv_test", "interv_test.tsglm" ] }, { "page": "invertinfo", "title": "Compute a Covariance Matrix from a Fisher Information Matrix", "topics": [ "invertinfo" ] }, { "page": "marcal", "title": "Predictive Model Assessment with a Marginal Calibration Plot", "topics": [ "marcal", "marcal.default", "marcal.tsglm" ] }, { "page": "measles", "title": "Measles Infections Time Series", "topics": [ "measles" ] }, { "page": "pit", "title": "Predictive Model Assessment with a Probability Integral Transform Histogram", "topics": [ "pit", "pit.default", "pit.tsglm" ] }, { "page": "plot.interv_detect", "title": "Plot Test Statistic of Intervention Detection Procedure for Count Time Series Following Generalised Linear Models", "topics": [ "plot.interv_detect" ] }, { "page": "plot.interv_multiple", "title": "Plot for Iterative Intervention Detection Procedure for Count Time Series following Generalised Linear Models", "topics": [ "plot.interv_multiple" ] }, { "page": "plot.tsglm", "title": "Diagnostic Plots for a Fitted GLM-type Model for Time Series of Counts", "topics": [ "plot.tsglm" ] }, { "page": "predict.tsglm", "title": "Predicts Method for Time Series of Counts Following Generalised Linear Models", "topics": [ "predict.tsglm" ] }, { "page": "QIC", "title": "Quasi Information Criterion of a Generalised Linear Model for Time Series of Counts", "topics": [ "QIC", "QIC.tsglm" ] }, { "page": "residuals.tsglm", "title": "Residuals of a Generalised Linear Model for Time Series of Counts", "topics": [ "residuals.tsglm" ] }, { "page": "scoring", "title": "Predictive Model Assessment with Proper Scoring Rules", "topics": [ "scoring", "scoring.default", "scoring.tsglm" ] }, { "page": "se.tsglm", "title": "Standard Errors of a Fitted Generalised Linear Model for Time Series of Counts", "topics": [ "se", "se.tsglm" ] }, { "page": "summary.tsglm", "title": "Summarising Fits of Count Time Series following Generalised Linear Models", "topics": [ "print.summary.tsglm", "summary.tsglm" ] }, { "page": "tsglm", "title": "Count Time Series Following Generalised Linear Models", "topics": [ "logLik.tsglm", "print.tsglm", "tsglm", "tsglm.meanfit", "vcov.tsglm" ] }, { "page": "tsglm.sim", "title": "Simulate a Time Series Following a Generalised Linear Model", "topics": [ "tsglm.sim" ] } ], "_rundeps": [ "ltsa" ], "_vignettes": [ { "source": "tsglm.Rnw", "filename": "tsglm.pdf", "title": "tscount: An R Package for Analysis of Count Time Series Following Generalized Linear Models", "engine": "utils::Sweave", "headings": [ "Introduction", "Models", "Estimation and inference", "Prediction", "Model assessment", "Intervention analysis", "Usage of the package", "Comparison with other software packages", "Outlook", "Implementation details", "Simulations" ], "created": "2015-02-06 16:46:31", "modified": "2020-09-07 20:19:04", "commits": 16 } ], "_score": 6.15380242962977, "_indexed": true, "_nocasepkg": "tscount", "_universes": [ "r-forge" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.4.4", "date": "2026-10-11T12:32:31.000Z", "distro": "resolute", "commit": "d4774dc5aa905ab969bf5d51faafaf51c0a3a431", "fileid": "https://r2.ropensci.org/ecf6acdafe04109f481b99ff489aead1fffd69cf4461360726a8bd36e74ecf17", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/r-forge/actions/runs/38139303459" }, { "r": "4.6.1", "os": "linux", "version": "1.4.4", "date": "2026-10-11T12:32:29.000Z", "distro": "resolute", "commit": "d4774dc5aa905ab969bf5d51faafaf51c0a3a431", "fileid": "https://r2.ropensci.org/4e8519d6c451fed0eded45302f4a5d678fe52efc7f38c50503c8d1ec825a111b", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/r-forge/actions/runs/38139303459" }, { "r": "4.5.3", "os": "mac", "version": "1.4.4", "date": "2026-10-11T12:32:05.000Z", "commit": "d4774dc5aa905ab969bf5d51faafaf51c0a3a431", "fileid": "https://r2.ropensci.org/23c7ddf4b4d0979c1eda0e9a996857ccf171521500c0e773a1099697fddfca5e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/r-forge/actions/runs/38139303459" }, { "r": "4.6.1", "os": "mac", "version": "1.4.4", "date": "2026-10-11T12:32:19.000Z", "commit": "d4774dc5aa905ab969bf5d51faafaf51c0a3a431", "fileid": "https://r2.ropensci.org/45c013712496f03802a135409c95a665a0d22989429adc86e8d8760c8c5695d6", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/r-forge/actions/runs/38139303459" }, { "r": "4.6.0", "os": "wasm", "version": "1.4.4", "date": "2026-10-11T12:32:36.000Z", "commit": "d4774dc5aa905ab969bf5d51faafaf51c0a3a431", "fileid": "https://r2.ropensci.org/86d0c3ba8ccb0d3d6abbe115d49d81990ab4e34238594985aa2197c7f36c082f", "status": "success", "buildurl": "https://github.com/r-universe/r-forge/actions/runs/38139303459" }, { "r": "4.7.0", "os": "win", "version": "1.4.4", "date": "2026-10-11T12:31:54.000Z", "commit": "d4774dc5aa905ab969bf5d51faafaf51c0a3a431", "fileid": "https://r2.ropensci.org/fbe2ff5aab33fc6372159924266f600e873f3948fc7ed45cd224095671495fbd", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/r-forge/actions/runs/38139303459" }, { "r": "4.5.3", "os": "win", "version": "1.4.4", "date": "2026-10-11T12:31:42.000Z", "commit": "d4774dc5aa905ab969bf5d51faafaf51c0a3a431", "fileid": "https://r2.ropensci.org/1cdb46801e36a91ece554269ae505b5cac2a7c0fbb9d89c8e59ded43c7188fae", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/r-forge/actions/runs/38139303459" }, { "r": "4.6.1", "os": "win", "version": "1.4.4", "date": "2026-10-11T12:32:09.000Z", "commit": "d4774dc5aa905ab969bf5d51faafaf51c0a3a431", "fileid": "https://r2.ropensci.org/dedd23198b8ad66cd8eee1868c4567f6757d56dea3b84fcfeed21cccb91ec5ee", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/r-forge/actions/runs/38139303459" } ] }