{ "_id": "6ab38ef83d719c1f840912e5", "Package": "holi", "Title": "Higher Order Likelihood Inference Web Applications", "Version": "0.1.1.9000", "Authors@R": "c(\nperson(\"Mackson\", \"Ncube\", , \"macksonncube.stats@gmail.com\", role = c(\"aut\", \"cre\")),\nperson(\"mightymetrika, LLC\", role = c(\"cph\", \"fnd\"))\n)", "Description": "Higher order likelihood inference is a promising approach\nfor analyzing small sample size data. The 'holi' package\nprovides web applications for higher order likelihood\ninference. It currently supports linear, logistic, and Poisson\ngeneralized linear models through the rstar_glm() function,\nbased on Pierce and Bellio (2017) and\n'likelihoodAsy'. The package offers two main features:\nLA_rstar(), which launches an interactive 'shiny' application\nallowing users to fit models with rstar_glm() through their web\nbrowser, and sim_rstar_glm_pgsql(), which streamlines the\nprocess of launching a web-based 'shiny' simulation application\nthat saves results to a user-created 'PostgreSQL' database.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.2", "URL": "https://github.com/mightymetrika/holi", "BugReports": "https://github.com/mightymetrika/holi/issues", "Config/testthat/edition": "3", "Config/pak/sysreqs": "cmake make libuv1-dev libpq-dev zlib1g-dev", "Repository": "https://mightymetrika.r-universe.dev", "Date/Publication": "2024-09-03 15:37:45 UTC", "RemoteUrl": "https://github.com/mightymetrika/holi", "RemoteRef": "HEAD", "RemoteSha": "6599efdaa53a1267bc54d4c3e4c2a787a7768745", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-23 08:30:43 UTC", "User": "root" }, "Author": "Mackson Ncube [aut, cre],\nmightymetrika, LLC [cph, fnd]", "Maintainer": "Mackson Ncube ", "_user": "mightymetrika", "_type": "src", "_file": "holi_0.1.1.9000.tar.gz", "_fileid": "https://r2.ropensci.org/0961843492de0b6df0be7899033bb30e5a0632b87fd811a12969313086266f5d", "_filesize": 115359, "_sha256": "0961843492de0b6df0be7899033bb30e5a0632b87fd811a12969313086266f5d", "_expires": "2027-01-01T08:33:58.000Z", "_created": "2026-09-23T08:30:43.000Z", "_published": "2026-09-23T08:34:00.331Z", "_jobs": [ { "job": 107104549149, "time": 142, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "10739559882" }, { "job": 107104549116, "time": 155, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "10739283736" }, { "job": 107104549192, "time": 113, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "10740001036" }, { "job": 107104549222, "time": 109, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", 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0.1.1.9000\n", "time": 1725377865 }, "_maintainer": { "name": "Mackson Ncube", "email": "macksonncube.stats@gmail.com", "login": "mightymetrika", "twitter": "@mightymetrika", "description": "", "uuid": 134214097 }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.1.0", "role": "Depends" }, { "package": "DT", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "likelihoodAsy", "role": "Imports" }, { "package": "MASS", "role": "Imports" }, { "package": "pool", "role": "Imports" }, { "package": "RPostgres", "role": "Imports" }, { "package": "shiny", "role": "Imports" }, { "package": "shinythemes", "role": "Imports" }, { "package": "sn", "role": "Imports" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" } ], "_owner": "mightymetrika", "_selfowned": true, "_usedby": 0, "_updates": [], "_tags": [], "_topics": [ "data", "data-science", "statistics" ], "_stars": 0, "_contributors": [ { "user": 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"page": "rstar_glm", "title": "Compute r* Statistics for Generalized Linear Models", "topics": [ "rstar_glm", "rstar_glm.default", "rstar_glm.linear", "rstar_glm.logistic", "rstar_glm.poisson" ] }, { "page": "run_sim_rstar_glm", "title": "Run Multiple Iterations of Simulation and Summarize Results", "topics": [ "run_sim_rstar_glm" ] }, { "page": "sim_rstar_glm", "title": "Simulate Data and Fit GLM and r* Models", "topics": [ "sim_rstar_glm" ] }, { "page": "sim_rstar_glm_pgsql", "title": "Shiny App for Running r* GLM Simulations with PostgreSQL Integration", "topics": [ "sim_rstar_glm_pgsql" ] } ], "_readme": "https://github.com/mightymetrika/holi/raw/HEAD/README.md", "_rundeps": [ "alabama", "base64enc", "bit", "bit64", "blob", "bslib", "cachem", "cli", "codetools", "commonmark", "cond", "cpp11", "crosstalk", "DBI", "digest", "DT", "evaluate", "farver", "fastmap", "fontawesome", "fs", "future", "future.apply", "generics", "ggplot2", "globals", "glue", "gtable", "highr", "hms", 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