{ "_id": "6ad46dfcdc7ca4d810c6cb29", "Package": "rsamplr", "Title": "Sampling Algorithms and Spatially Balanced Sampling", "Version": "0.2.0", "Authors@R": "c(\nperson(\"Wilmer\", \"Prentius\", , \"wilmer.prentius@slu.se\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-3561-290X\")),\nperson(\"Anton\", \"Grafström\", role = \"ctb\",\ncomment = c(ORCID = \"0000-0002-4345-4024\")),\nperson(\"Authors of the dependent Rust crates\", role = \"aut\",\ncomment = \"see inst/AUTHORS file\")\n)", "Description": "Fast tools for unequal probability sampling in\nmulti-dimensional spaces, implemented in Rust for high\nperformance. The package offers a wide range of methods,\nincluding Sampford (Sampford, 1967,\n) and correlated Poisson\nsampling (Bondesson and Thorburn, 2008,\n), pivotal sampling\n(Deville and Tillé, 1998, ), and\nbalanced sampling such as the cube method (Deville and Tillé,\n2004, ) to ensure auxiliary totals\nare respected. Spatially balanced approaches, including the\nlocal pivotal method (Grafström et al., 2012,\n), spatially correlated\nPoisson sampling (Grafström, 2012,\n), and locally correlated\nPoisson sampling (Prentius, 2024, ),\nprovide efficient designs when the target variable is linked to\nauxiliary information.", "URL": "https://www.envisim.se/, https://github.com/envisim/rust-samplr/", "BugReports": "https://github.com/envisim/rust-samplr/issues", "License": "AGPL-3", "Encoding": "UTF-8", "Language": "en-GB", "RoxygenNote": "7.3.3", "SystemRequirements": "Cargo (Rust's package manager), rustc >= 1.84.1", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-10-18 06:39:07 UTC", "User": "root" }, "Author": "Wilmer Prentius [aut, cre] (ORCID:\n), Anton Grafström [ctb]\n(ORCID: ), Authors of\nthe dependent Rust crates [aut] (see inst/AUTHORS file)", "Maintainer": "Wilmer Prentius ", "Config/pak/sysreqs": "libclang-dev", "Repository": "https://wpmg.r-universe.dev", "Date/Publication": 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