{ "_id": "6a25187c4b233be19838c825", "Type": "Package", "Package": "qPRAentry", "Title": "Quantitative Pest Risk Assessment at the Entry Step", "Version": "0.1.0", "Authors@R": "c(\nperson(given = \"Martina\", family = \"Cendoya\", email = \"cendoya_marmar@gva.es\",\nrole = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-0134-7781\")),\nperson(given = \"Maria Chiara\", family = \"Rosace\", email = \"mariachiara.rosace@unicatt.it\",\nrole = \"aut\", comment = c(ORCID = \"0000-0002-7263-8228\"))\n)", "Description": "Supports risk assessors in performing the entry step of\nthe quantitative Pest Risk Assessment. It allows the estimation\nof the amount of a plant pest entering a risk assessment area\n(in terms of founder populations) through the calculation of\nthe imported commodities that could be potential pathways of\npest entry, and the development of a pathway model. Two 'Shiny'\napps based on the functionalities of the package are included,\nthat simplify the process of assessing the risk of entry of\nplant pests. The approach is based on the work of the European\nFood Safety Authority (EFSA PLH Panel et al., 2018)\n.", "License": "GPL (>= 3)", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Encoding": "UTF-8", "LazyData": "true", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.2", "Config/pak/sysreqs": "libabsl-dev libcairo2-dev cmake libfontconfig1-dev\nlibfreetype6-dev libgdal-dev gdal-bin libgeos-dev make\nlibicu-dev libpng-dev libuv1-dev libxml2-dev libssl-dev\nlibproj-dev libsqlite3-dev libudunits2-dev libx11-dev\nzlib1g-dev", "Repository": "https://mcendoya.r-universe.dev", "Date/Publication": "2025-09-23 16:24:37 UTC", "RemoteUrl": "https://github.com/mcendoya/qpraentry", "RemoteRef": "HEAD", "RemoteSha": "50e37ea29990699db50b76eb87013585f862c792", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-07 07:01:26 UTC", "User": "root" }, "Author": "Martina Cendoya [aut, cre] (ORCID:\n),\nMaria Chiara Rosace [aut] (ORCID:\n)", "Maintainer": "Martina Cendoya ", 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"0000-0002-0134-7781" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 2.10", "role": "Depends" }, { "package": "bsplus", "role": "Imports" }, { "package": "dplyr", "role": "Imports" }, { "package": "DT", "role": "Imports" }, { "package": "eurostat", "version": ">= 4.0.0", "role": "Imports" }, { "package": "ggiraph", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "giscoR", "version": ">= 0.6.0", "role": "Imports" }, { "package": "memoise", "role": "Imports" }, { "package": "purrr", "role": "Imports" }, { "package": "sf", "role": "Imports" }, { "package": "shiny", "role": "Imports" }, { "package": "shinycssloaders", "role": "Imports" }, { "package": "shinyjs", "role": "Imports" }, { "package": "shinyWidgets", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "tidyr", "role": "Imports" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "testthat", 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Example using ISO codes", "A.1. Trade data preparation", "Structure of trade data", "Generation of the TradeData object from the above data frames", "A.2. $N_", "Calculation of the $N_{trade}$ for each time period", "$N_{trade}$ summary for the time periods", "A.3. $N_", "A.4. Pathway model", "B. Example using NUTS codes", "B.1. Trade data preparation", "B.2. $N_", "B.3. $N_", "Redistribution using Eurostat human population data from NUTS0 to NUTS2", "Redistribution providing values from NUTS0 to NUTS1", "B.4. 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