{ "_id": "6ac4ccc6f511ae58c09a185b", "Package": "vpc", "Title": "Create Visual Predictive Checks", "Version": "1.2.4", "Date": "2026-02-10", "Authors@R": "c(\nperson(\"Ron\", \"Keizer\", email=\"ron@insight-rx.com\", role=c(\"aut\", \"cre\")),\nperson(\"Bill\", \"Denney\", email=\"wdenney@humanpredictions.com\", role=\"aut\", comment=c(ORCID=\"0000-0002-5759-428X\"))\n)", "Maintainer": "Ron Keizer ", "Description": "Visual predictive checks are a commonly used diagnostic\nplot in pharmacometrics, showing how certain statistics\n(percentiles) for observed data compare to those same\nstatistics for data simulated from a model. The package can\ngenerate VPCs for continuous, categorical, censored, and\n(repeated) time-to-event data.", "License": "MIT + file LICENSE", "LazyData": "true", "URL": "https://github.com/ronkeizer/vpc", "RoxygenNote": "7.3.3", "Encoding": "UTF-8", "Config/testthat/edition": "3", "Config/pak/sysreqs": "libicu-dev libx11-dev", "Repository": "https://ronkeizer.r-universe.dev", "Date/Publication": "2026-02-28 17:03:06 UTC", "RemoteUrl": "https://github.com/ronkeizer/vpc", "RemoteRef": "HEAD", "RemoteSha": "b1d6a72217552a45d321ace2b7fa40af74eca5fa", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-06 10:21:49 UTC", "User": "root" }, "Author": "Ron Keizer [aut, cre],\nBill Denney [aut] (ORCID: )", "_user": "ronkeizer", "_type": "src", "_file": "vpc_1.2.4.tar.gz", "_fileid": "https://r2.ropensci.org/381f0d1781fe055ed8a36eb52efe79479d8ae413e9c47978cd9dc08f549e574c", "_filesize": 830310, "_sha256": "381f0d1781fe055ed8a36eb52efe79479d8ae413e9c47978cd9dc08f549e574c", "_expires": 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"auto_bin", "auto_bin.data.frame", "auto_bin.numeric" ] }, { "page": "bin_data", "title": "Function to bin data based on a vector of bin separators, e.g. for use in VPC", "topics": [ "bin_data" ] }, { "page": "calc_pred_corr_continuous", "title": "Perform prediction-correction", "topics": [ "calc_pred_corr_continuous" ] }, { "page": "calc_vpc_continuous", "title": "Calculate aggregate statistics for simulated and observed VPC data", "topics": [ "calc_vpc_continuous" ] }, { "page": "check_stratification_columns_available", "title": "Check whether stratification columns are available", "topics": [ "check_stratification_columns_available" ] }, { "page": "compute_kaplan", "title": "Compute Kaplan-Meier statistics", "topics": [ "compute_kaplan" ] }, { "page": "compute_kmmc", "title": "Compute KMMC statistics", "topics": [ "compute_kmmc" ] }, { "page": "create_vpc_theme", "title": "Create new vpc theme", "topics": [ "create_vpc_theme" ] }, { "page": "define_bins", "title": "Define bins for many types of data", "topics": [ "define_bins", "define_bins_tte" ] }, { "page": "define_data_columns", "title": "Define data column defaults for various softwares", "topics": [ "define_data_columns" ] }, { "page": "define_loq", "title": "Check and standardize limits of quantification", "topics": [ "define_loq" ] }, { "page": "draw_params_mvr", "title": "Draw parameters from multivariate distribution", "topics": [ "draw_params_mvr" ] }, { "page": "filter_dv", "title": "Remove values that are not observed values from data", "topics": [ "filter_dv" ] }, { "page": "format_vpc_input_data", "title": "Prepare VPC data for future calculations by standardizing column names and modifying the input data based on the limits of quantification, stratification, and logarithmic values.", "topics": [ "format_vpc_input_data", "format_vpc_input_data_tte" ] }, { "page": "ggplot.vpcdb_continuous", "title": "Create a ggplot for each vpcdb type", "topics": [ "ggplot.vpcdb_categorical", 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