{"Package":"wdm","Title":"Weighted Dependence Measures","Version":"0.2.4","Authors@R":"person(\"Thomas\", \"Nagler\", email = \"mail@tnagler.com\", role = c(\"aut\", \"cre\"))","Description":"Provides efficient implementations of weighted dependence measures\nand related asymptotic tests for independence. Implemented measures are\nthe Pearson correlation, Spearman's rho, Kendall's tau, Blomqvist's beta, and\nHoeffding's D; see, e.g., Nelsen (2006) and\nHollander et al. (2015, ISBN:9780470387375).","Depends":"R (>= 3.2.0)","License":"MIT + file LICENSE","Encoding":"UTF-8","LinkingTo":"Rcpp","Imports":"Rcpp","RoxygenNote":"7.2.3","URL":"https://github.com/tnagler/wdm-r","BugReports":"https://github.com/tnagler/wdm-r/issues","Suggests":"testthat, Hmisc, copula, covr","NeedsCompilation":"yes","Packaged":"2023-08-10 06:33:37 UTC; n5","Author":"Thomas Nagler [aut, cre]","Maintainer":"Thomas Nagler ","Repository":"CRAN","Date/Publication":"2023-08-10 17:20:02 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/wdm_0.2.4.tar.gz","jsonAuthors":[{"name":"Thomas Nagler","email":"mail@tnagler.com","maintainer":true}],"readme":"\n# wdm\n\n[![R-CMD-check](https://github.com/tnagler/wdm-r/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/tnagler/wdm-r/actions/workflows/R-CMD-check.yaml)\n[![CRAN\nstatus](https://www.r-pkg.org/badges/version/wdm)](https://cran.r-project.org/package=wdm)\n![CRAN downloads](http://cranlogs.r-pkg.org/badges/wdm)\n\nR interface to the [wdm](https://github.com/tnagler/wdm) C++ library,\nwhich provides efficient implementations of weighted dependence measures\nand related independence tests:\n\n- Pearsons’s rho\n- Spearmans’s rho\n- Kendall’s tau\n- Blomqvist’s beta\n- Hoeffding’s D\n\nAll measures are computed in *O(n* log *n)* time, where *n* is the\nnumber of observations.\n\nFor a detailed description of the functionality, see the [API\ndocumentation](https://tnagler.github.io/wdm-r/).\n\n### Installation\n\n- the stable release from CRAN:\n\n``` r\ninstall.packages(\"wdm\")\n```\n\n- the development version from [GitHub](https://github.com/) with:\n\n``` r\n# install.packages(\"devtools\")\ninstall_submodule_git <- function(x, ...) {\n install_dir <- tempfile()\n system(paste(\"git clone --recursive\", shQuote(x), shQuote(install_dir)))\n devtools::install(install_dir, ...)\n}\ninstall_submodule_git(\"https://github.com/tnagler/wdm-r\")\n```\n\n### Cloning\n\nThis repo contains [wdm](https://github.com/tnagler/wdm) as a submodule.\nFor a full clone use\n\n``` shell\ngit clone --recurse-submodules \n```\n\n### Examples\n\n``` r\nlibrary(wdm)\n```\n\n##### Dependence between two vectors\n\n``` r\nx <- rnorm(100)\ny <- rpois(100, 1) # all but Hoeffding's D can handle ties\nw <- runif(100)\nwdm(x, y, method = \"kendall\") # unweighted\n#> [1] -0.03093257\nwdm(x, y, method = \"kendall\", weights = w) # weighted\n#> [1] 0.04835766\n```\n\n##### Dependence in a matrix\n\n``` r\nx <- matrix(rnorm(100 * 3), 100, 3)\nwdm(x, method = \"spearman\") # unweighted\n#> [,1] [,2] [,3]\n#> [1,] 1.00000000 0.2194659 -0.05435344\n#> [2,] 0.21946595 1.0000000 0.11401140\n#> [3,] -0.05435344 0.1140114 1.00000000\nwdm(x, method = \"spearman\", weights = w) # weighted\n#> [,1] [,2] [,3]\n#> [1,] 1.0000000 0.2575236 -0.1689466\n#> [2,] 0.2575236 1.0000000 0.1197442\n#> [3,] -0.1689466 0.1197442 1.0000000\n```\n\n##### Independence test\n\n``` r\nx <- rnorm(100)\ny <- rpois(100, 1) # all but Hoeffding's D can handle ties\nw <- runif(100)\nindep_test(x, y, method = \"kendall\") # unweighted\n#> estimate statistic p_value n_eff method alternative\n#> 1 0.1278922 1.532215 0.1254693 100 kendall two-sided\nindep_test(x, y, method = \"kendall\", weights = w) # weighted\n#> estimate statistic p_value n_eff method alternative\n#> 1 0.1704296 1.779486 0.07516007 79.6939 kendall two-sided\n```","jobInfo":{"package":"wdm","version":"0.2.4","parsingStatus":"success","parserVersion":2,"parsedAt":"2025-01-07T21:29:57+0000"}}

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