{"Package":"Iscores","Type":"Package","Title":"Proper Scoring Rules for Missing Value Imputation","Version":"1.1.0","Author":"Loris Michel, Meta-Lina Spohn, Jeffrey Naef","Maintainer":"Loris Michel ","Description":"Implementation of a KL-based scoring rule to assess the quality of different missing value imputations in the broad sense as introduced in Michel et al. (2021) .","License":"GPL-3","Encoding":"UTF-8","RoxygenNote":"7.1.1","Depends":"parallel, stats, ranger, kernlab","NeedsCompilation":"no","Packaged":"2021-12-24 08:29:47 UTC; lorismichel","Repository":"CRAN","Date/Publication":"2022-01-05 00:00:08 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/Iscores_1.1.0.tar.gz","readme":"# Iscores: scoring imputations methods\n\n\n## Overview\n\nIscores is a package intended to provide a framework for scoring imputations methods. It implements the scores described in [Michel, Naef, Spohn and Meinshausen. 2021](https://arxiv.org/abs/2106.03742) . Examples of use of the library are shown below.\n\n\n## Installation\n\nThe package should be (soon) available on CRAN, To install the package from github you can run\n\n``` r\ninstall.packages(\"devtools\")\ndevtools::install_github(\"missValTeam/Iscores\")\n```\n\n## Examples: \n\n\n```r\nn <- 20\nX <- cbind(rnorm(n),rnorm(n))\nX.NA <- X\nX.NA[,1] <- ifelse(runif(n)<=0.2, NA, X[,1])\n\nimputations <- list()\n\nimputations[[1]] <- lapply(1:5, function(i) {\n X.loc <- X.NA\n X.loc[is.na(X.NA[,1]),1] <- mean(X.NA[,1],na.rm=TRUE)\n return(X.loc)\n})\n\nimputations[[2]] <- lapply(1:5, function(i) {\n X.loc <- X.NA\n X.loc[is.na(X.NA[,1]),1] <- sample(X.NA[!is.na(X.NA[,1]),1], size = sum(is.na(X.NA[,1])), replace = TRUE)\n return(X.loc)\n})\n\nmethods <- c(\"mean\",\"sample\")\n\nIscores(imputations = imputations, methods = methods, X.NA = X.NA)\n```\n\n\n## Issues\n\nTo report an issue, please use the [issue tracker](https://github.com/missValTeam/Iscores/issues) on github.com.","jobInfo":{"package":"Iscores","version":"1.1.0","parsingStatus":"success","parserVersion":1,"parsedAt":"2022-01-05T01:30:32+0000"}}

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