{ "_id": "6a104a86acfb0bcc41c9fb38", "Package": "NonParRolCor", "Type": "Package", "Title": "a Non-Parametric Statistical Significance Test for Rolling\nWindow Correlation", "Version": "0.8.0", "Authors@R": "c(person(given = \"Josue M.\", family = \"Polanco-Martinez\", role = c(\"aut\", \"cph\", \"cre\"), email = \"josue.m.polanco@gmail.com\", comment = c(ORCID = \"0000-0001-7164-0185\")), person(given = \"Jose L.\", family = \"Lopez-Martinez\", role = c(\"ctb\"), email = \"jose.lopez@correo.uady.mx\", comment = c(ORCID = \"0000-0002-2489-7559\")))", "Maintainer": "Josue M. Polanco-Martinez ", "Description": "Estimates and plots (as a single plot and as a heat map)\nthe rolling window correlation coefficients between two time\nseries and computes their statistical significance, which is\ncarried out through a non-parametric computing-intensive\nmethod. This method addresses the effects due to the multiple\ntesting (inflation of the Type I error) when the statistical\nsignificance is estimated for the rolling window correlation\ncoefficients. The method is based on Monte Carlo simulations by\npermuting one of the variables (e.g., the dependent) under\nanalysis and keeping fixed the other variable (e.g., the\nindependent). We improve the computational efficiency of this\nmethod to reduce the computation time through parallel\ncomputing. The 'NonParRolCor' package also provides examples\nwith synthetic and real-life environmental time series to\nexemplify its use. Methods derived from R. Telford (2013)\n and J.M.\nPolanco-Martinez and J.L. Lopez-Martinez (2021)\n.", "License": "GPL (>= 2)", "Encoding": "UTF-8", "LazyData": "true", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-10 08:09:45 UTC", "User": "root" }, "Author": "Josue M. Polanco-Martinez [aut, cph, cre]\n(), Jose L.\nLopez-Martinez [ctb] ()", "Repository": "https://jomopo.r-universe.dev", "Date/Publication": "2022-10-30 20:03:03 UTC", "RemoteUrl": "https://github.com/cran/NonParRolCor", "RemoteRef": "HEAD", "RemoteSha": "b4dabc9a36797008f58605f5d3e9eea80cd4bb6a", "MD5sum": "7ab474b8bda1906616f9e1210982bb31", "_user": "jomopo", "_type": "src", "_file": "NonParRolCor_0.8.0.tar.gz", "_fileid": "77af62e896be552193d215e3a39d490644f6f5d3d8bfb1b5d314a7b83e1b69f1", "_filesize": 185256, "_sha256": "77af62e896be552193d215e3a39d490644f6f5d3d8bfb1b5d314a7b83e1b69f1", "_created": "2026-05-10T08:09:45.000Z", "_published": "2026-05-22T12:22:30.154Z", "_distro": "noble", "_jobs": [ { "job": 77378472422, "time": 131, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "6902208551" }, { "job": 77378472553, "time": 121, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "6902207661" }, { "job": 77378472492, "time": 101, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "6902205790" }, { "job": 77378472344, "time": 88, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "6902204407" }, { "job": 77378471946, "time": 180, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "6902195760" }, { "job": 77378471758, "time": 85, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7160354293" }, { "job": 77378472434, "time": 270, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "6902222004" }, { "job": 77378472626, "time": 81, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "6902203823" }, { "job": 77378472814, "time": 69, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "6902202702" } ], "_buildurl": "https://github.com/r-universe/jomopo/actions/runs/25623639491", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/NonParRolCor", "_commit": { "id": "b4dabc9a36797008f58605f5d3e9eea80cd4bb6a", "author": "Josue M. 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rolling correlation coefficients that are statistically significant", "topics": [ "plot_rolcor_estim_heatmap" ] }, { "page": "estimation_1win", "title": "Estimates the rolling window correlation coefficients for only one window-length and their statistical significance", "topics": [ "rolcor_estim_1win" ] }, { "page": "estimation_heatmap", "title": "Estimates the rolling window correlation coefficients for several window-lengths and their statistical significance", "topics": [ "rolcor_estim_heatmap" ] }, { "page": "syntheticdata", "title": "Synthetic data set to exemplify the use of the functions contained in _NonParRolCor_", "topics": [ "syntheticdata" ] } ], "_rundeps": [ "cli", "codetools", "colorspace", "doParallel", "farver", "foreach", "glue", "gtools", "iterators", "labeling", "lifecycle", "pracma", "R6", "RColorBrewer", "rlang", "scales", "viridisLite" ], "_score": 1, "_indexed": true, "_nocasepkg": "nonparrolcor", "_universes": [ "jomopo" ], "_binaries": [ { "r": "4.7.0", "os": 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