{ "_id": "6a4792f79c870a7243dbd01e", "Package": "coconots", "Type": "Package", "Title": "Convolution-Closed Models for Count Time Series", "Version": "2.0.3", "Date": "2026-06-14", "Authors@R": "c(\nperson(given = \"Manuel\",\nfamily = \"Huth\",\nrole = c(\"aut\", \"cre\"),\nemail = \"manuel.huth@yahoo.com\"),\nperson(given = \"Robert C.\",\nfamily = \"Jung\",\nrole = \"aut\"),\nperson(given = \"Andy\",\nfamily = \"Tremayne\",\nrole = \"aut\"\n))", "Description": "Useful tools for fitting, validating, and forecasting of\npractical convolution-closed time series models for low counts\nare provided. Marginal distributions of the data can be\nmodelled via Poisson and Generalized Poisson innovations.\nRegression effects can be incorporated through time varying\ninnovation rates. The models are described in Jung and Tremayne\n(2011) and the model\nassessment tools are presented in Czado et al. (2009)\n and, Tsay (1992)\n.", "URL": "https://github.com/manuhuth/coconots,\nhttps://manuhuth.github.io/coconots/", "BugReports": "https://github.com/manuhuth/coconots/issues", "LazyData": "true", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "Config/testthat/edition": "3", "Config/Needs/website": "pkgdown", "License": "MIT + file LICENSE", "Repository": "https://manuhuth.r-universe.dev", "Date/Publication": "2026-07-02 15:00:24 UTC", "RemoteUrl": "https://github.com/manuhuth/coconots", "RemoteRef": "HEAD", "RemoteSha": "67db28e2ffc447763e0481cd5c3b238c247530e6", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-07-02 15:17:01 UTC", "User": "root" }, "Author": "Manuel Huth [aut, cre],\nRobert C. Jung [aut],\nAndy Tremayne [aut]", "Maintainer": "Manuel Huth ", "_user": "manuhuth", "_type": "src", "_file": "coconots_2.0.3.tar.gz", "_fileid": "https://r2.ropensci.org/9399a93ce2831f7c3b6aa4606e0ec3aa9b8d7c64e8c191eee5ccecd77db637ea", "_filesize": 988761, "_sha256": "9399a93ce2831f7c3b6aa4606e0ec3aa9b8d7c64e8c191eee5ccecd77db637ea", "_expires": "2026-10-11T10:46:14.000Z", "_created": "2026-07-02T15:17:01.000Z", "_published": "2026-07-03T10:46:15.690Z", "_jobs": [ { "job": 84983553499, "time": 167, "config": "linux-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": "8043399422" }, { "job": 84983553590, "time": 158, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "8043396291" }, { "job": 84983553777, "time": 152, "config": "linux-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "8043393085" }, { "job": 84983553531, "time": 149, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "8043393059" }, { "job": 84983553532, "time": 127, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "8043380134" }, { "job": 84983553430, "time": 264, "config": "macos-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "8043442179" }, { "job": 84983553701, "time": 129, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "8043381418" }, { "job": 84983553413, "time": 206, "config": "macos-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "8043423367" }, { "job": 84983553485, "time": 184, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "8043320756" }, { "job": 84983553506, "time": 152, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "8043394647" }, { "job": 84983553574, "time": 149, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "8043389730" }, { "job": 84983553495, "time": 161, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "8043398533" }, { "job": 84983553399, "time": 164, "config": "windows-release", "r": "4.6.1", "check": "OK", "artifact": "8043397111" } ], "_host": "GitHub-Actions", "_buildurl": "https://github.com/r-universe/manuhuth/actions/runs/28600907678", "_status": "success", "_upstream": "https://github.com/manuhuth/coconots", "_commit": { "id": "67db28e2ffc447763e0481cd5c3b238c247530e6", "author": "Manuel Huth <64041311+manuhuth@users.noreply.github.com>", "committer": "GitHub ", "message": "Multithread the order-2 likelihood kernels on the RCPP backend (#10)\n\nlikelihoodGP2 and likelihoodGP2cov now take a cores argument and\nparallelize via std::thread (no OpenMP, no new dependencies): the\nno-covariate path builds the distinct-(y,z) g-vector cache concurrently\nover read-only tables, the covariate path computes per-t log-terms with\nthread-private tables into a preallocated vector. Accumulation stays\nserial in the original order, so results are bit-identical for any\nthread count (verified against a pre-change build: NLL values, fitted\nparameters, and log-likelihoods all match exactly).\n\ncocoReg's previously dead cores argument is now live and flows down to\nthe kernels; it defaults to physical cores - 1 (mirroring the\nJULIA_NUM_THREADS convention) and is capped at 2 while\n_R_CHECK_LIMIT_CORES_ is set so CRAN checks stay policy-compliant.\nWorker threads never touch the R API; the only stop() condition is\nchecked on the main thread before spawning. Order-1 kernels are\nmicrosecond-scale and stay serial. src/Makevars{,.win} add -pthread.\n\nMeasured on 14 physical cores (T = 1000, GP2): full cocoReg fits drop\nfrom 6.3 s to 1.1 s (no covariates) and from 11.4 s to 1.5 s (with\ncovariates); single NLL calls scale 6.4x / 8.4x at 13 threads.\n\nCo-authored-by: Claude Fable 5 ", "time": 1783004424 }, "_maintainer": { "name": "Manuel Huth", "email": "manuel.huth@yahoo.com", "login": "manuhuth", "uuid": 64041311 }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.0.2", "role": "Depends" }, { "package": "Rcpp", "role": "LinkingTo" }, { "package": "forecast", "role": "Imports" }, { "package": "numDeriv", "role": "Imports" }, { "package": "HMMpa", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "matrixStats", "role": "Imports" }, { "package": "JuliaConnectoR", "role": "Imports" }, { "package": "parallel", "role": "Imports" }, { "package": "Rcpp", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" } ], "_owner": "manuhuth", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-28", "n": 1 }, { "week": "2025-30", "n": 3 }, { "week": "2025-34", "n": 3 }, { "week": "2026-23", "n": 2 }, { "week": "2026-24", "n": 1 }, { "week": "2026-25", "n": 6 }, { "week": "2026-27", "n": 3 } ], "_tags": [], "_stars": 4, "_contributors": [ { "user": "manuhuth", "count": 175, "uuid": 64041311 }, { "user": "rcjung", "count": 8, "uuid": 173567028 } ], "_userbio": { "uuid": 64041311, "type": "user", "name": "Manuel Huth", "followers": 31, "description": "PhD candidate in Mathematics with a focus on Computational Methods." }, "_downloads": { "count": 639, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/coconots" }, "_devurl": "https://github.com/manuhuth/coconots", "_pkgdown": "https://manuhuth.github.io/coconots/", "_searchresults": 4, "_topics": [ "cpp" 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Collecting Wage Loss Benefit", "object": "cuts", "class": [ "ts" ], "fields": [], "table": false, "tojson": true }, { "name": "downloads", "title": "Time Series of Daily Downloads of a TeX-Editor", "object": "downloads", "class": [ "ts" ], "fields": [], "table": false, "tojson": true }, { "name": "goldparticle", "title": "Time Series of Gold Particle Counts in a Well-Defined Colloidal Solution", "object": "goldparticle", "class": [ "ts" ], "fields": [], "table": false, "tojson": true } ], "_help": [ { "page": "cocoBoot", "title": "Bootstrap Based Model Assessment Procedure", "topics": [ "cocoBoot" ] }, { "page": "cocoPit", "title": "Probability Integral Transform Based Model Assessment Procedure", "topics": [ "cocoPit" ] }, { "page": "cocoReg", "title": "Fitting First- and Second Order (G)PAR Models", "topics": [ "cocoReg" ] }, { "page": "cocoResid", "title": "Residual Based Model Assessment Procedure", "topics": [ "cocoResid" ] }, { "page": "cocoScore", "title": "Scoring Rule Based Model Assessment Procedure", "topics": [ "cocoScore" ] }, { "page": "cocoSim", "title": "Simulation of Count Time Series", "topics": [ "cocoSim" ] }, { "page": "cocoSoc", "title": "Computes Scores for Various Models Maintaining a Common Sample", "topics": [ "cocoSoc" ] }, { "page": "cuts", "title": "Time Series of Monthly Counts of Claimants Collecting Wage Loss Benefit", "topics": [ "cuts" ] }, { "page": "downloads", "title": "Time Series of Daily Downloads of a TeX-Editor", "topics": [ "downloads" ] }, { "page": "goldparticle", "title": "Time Series of Gold Particle Counts in a Well-Defined Colloidal Solution", "topics": [ "goldparticle" ] }, { "page": "installJuliaPackages", "title": "installJuliaPackages", "topics": [ "installJuliaPackages" ] }, { "page": "predict.coco", "title": "K-Step Ahead Forecast Distributions", "topics": [ "predict.coco" ] }, { "page": "setJuliaSeed", "title": "Set Seed for julia's Random Number Generator", "topics": [ "setJuliaSeed" ] } ], "_readme": 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