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This multivariate analysis\nhelps to characterize levels of dissimilarity between a set of\nconditions of reference and another set of conditions of\ninterest. If predictive models are transferred to conditions\ndifferent from those over which models were calibrated\n(trained), this metric helps to identify transfer conditions\nthat differ substantially from those of calibration. These\ntools are implemented following principles proposed in Owens et\nal. (2013) , and expanded\nto obtain more detailed results that aid in interpretation as\nin Cobos et al. (2024) .", "URL": "https://github.com/marlonecobos/mop", "BugReports": "https://github.com/marlonecobos/mop/issues", "License": "GPL (>= 3)", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.2", "LazyData": "true", "SystemRequirements": "C++17", "Config/pak/sysreqs": "libgdal-dev gdal-bin libgeos-dev libproj-dev\nlibsqlite3-dev", "Repository": "https://marlonecobos.r-universe.dev", "Date/Publication": "2026-04-22 14:18:44 UTC", "RemoteUrl": "https://github.com/marlonecobos/mop", "RemoteRef": "HEAD", "RemoteSha": "fec67e8ee15a38c6a2b955c012afecb88dc6c439", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-22 09:05:01 UTC", "User": "root" }, "Author": "Marlon E. Cobos [aut, cre] (ORCID:\n),\nHannah L. Owens [aut] (ORCID: ),\nJorge Soberón [aut] (ORCID: ),\nA. 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