{ "_id": "6a105126acfb0bcc41ca1387", "Package": "kvr2", "Type": "Package", "Title": "Calculate and Compare Multiple Definitions of Coefficient of\nDetermination", "Version": "0.2.0.9000", "Authors@R": "c(\nperson(\n\"Mao\", \"Kobayashi\",\nemail = \"kobamao.jp@gmail.com\",\nrole = c(\"aut\", \"cre\")\n)\n)", "Description": "Calculate nine types of coefficients of determination\n(R-squared) based on the classification by Kvalseth (1985)\n. This package is designed\nfor educational purposes to demonstrate how R-squared values\ncan fluctuate depending on the choice of formula, particularly\nin power regression models or linear models without an\nintercept. By providing a comprehensive list of definitions, it\nhelps users understand the mathematical sensitivity of\ngoodness-of-fit indices.", "URL": "https://github.com/indenkun/kvr2, https://indenkun.github.io/kvr2/", "BugReports": "https://github.com/indenkun/kvr2/issues", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "RoxygenNote": "7.3.3", "Roxygen": "list(markdown = TRUE)", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://indenkun.r-universe.dev", "Date/Publication": "2026-03-11 01:15:13 UTC", "RemoteUrl": "https://github.com/indenkun/kvr2", "RemoteRef": "HEAD", "RemoteSha": "5df8d5dc85d67bdf4c11b3709e3e92c555a0b9c1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-10 05:11:49 UTC", "User": "root" }, "Author": "Mao Kobayashi [aut, cre]", "Maintainer": "Mao Kobayashi ", "MD5sum": "43eb42e1dfb261f6430d1baf3a51e3bd", "_user": "indenkun", "_type": "src", "_file": "kvr2_0.2.0.9000.tar.gz", "_fileid": 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"page": "plot_diagnostic", "title": "Plot Observed vs Predicted Values", "topics": [ "plot_diagnostic" ] }, { "page": "plot_kvr2", "title": "Plot Method for Kvalseth's R-squared Objects", "topics": [ "plot_kvr2" ] }, { "page": "plot.comp_model", "title": "Plot Comparison of Model Specifications", "topics": [ "plot.comp_model" ] }, { "page": "plot.r2_kvr2", "title": "Plot Method for r2_kvr2 Objects", "topics": [ "plot.r2_kvr2" ] }, { "page": "print.comp_model", "title": "Print Method for Model Comparison Objects", "topics": [ "print.comp_model" ] }, { "page": "print.kvr2", "title": "Print Methods for r2 and comp_fit calculation Objects", "topics": [ "print.comp_kvr2", "print.r2_kvr2" ] }, { "page": "r2_kvr2", "title": "Calculate Multiple Definitions of Coefficient of Determination (R-squared)", "topics": [ "r2", "r2_1", "r2_2", "r2_3", "r2_4", "r2_5", "r2_6", "r2_7", "r2_8", "r2_9" ] }, { "page": "r2_adjusted", "title": "Calculate the Adjusted Determination Coefficient", "topics": [ "r2_adjusted" ] } ], "_readme": "https://github.com/indenkun/kvr2/raw/HEAD/README.md", "_rundeps": [ "cli", "cpp11", "dplyr", "farver", "generics", "ggplot2", "glue", "gtable", "insight", "isoband", "labeling", "lifecycle", "magrittr", "pillar", "pkgconfig", "purrr", "R6", "RColorBrewer", "rlang", "S7", "scales", "stringi", "stringr", "tibble", "tidyr", "tidyselect", "utf8", "vctrs", "viridisLite", "withr" ], "_vignettes": [ { "source": "internal-design.Rmd", "filename": "internal-design.html", "title": "Internal Design", "engine": "knitr::rmarkdown", "headings": [ "Internal Design of kvr2", "Overview", "Data Flow Architecture", "1. Extraction Phase (values_lm)", "2. Computation and Metadata Injection (r2, comp_model)", "3. Dispatch and Visualization Phase", "Handling Non-Standard Evaluation (NSE)", "Dependency Strategy", "Troubleshooting and Maintenance" ], "created": "2026-02-24 07:17:04", "modified": "2026-03-10 11:23:56", "commits": 2 }, { "source": "Pitfalls_of_R2.Rmd", "filename": "Pitfalls_of_R2.html", "title": "The Pitfalls of R-squared: Understanding Mathematical Sensitivity", "engine": "knitr::rmarkdown", "headings": [ "Introduction: Why $R^2$ is Not Unique", "The Eight + One Definitions", "Standard Definitions", "Definitions for No-Intercept Models", "Robust Definition", "When $R^2$ Goes Negative: Interpretation and Risks", "Meaning of Negative Values", "Case Study: Forcing a No-Intercept Model", "The Transformation Trap (Power Models)", "Distinguishing Variable Names from Functions", "Transparency and Metadata: Beyond the Numbers", "Inspecting Model Information", "Enhanced Console Output", "Technical Note: How R Calculates", "The Shift in Baseline", "Case Study: The Danger of No-Intercept Models", "The Trap", "Visualizing the Sensitivity of R-squared", "Comparing Intercept vs. No-Intercept Models", "Practical Example: The Sensitivity of $R^2$", "1. 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