{ "_id": "6a250e5f4b233be198388c40", "Package": "fields", "Version": "17.4", "Date": "2026-05-05", "Title": "Tools for Spatial Data", "Authors@R": "c( person(\"Douglas\", \"Nychka\", role = c(\"aut\", \"cre\"),\nemail = \"douglasnychka@gmail.com\"),\nperson(\"Reinhard\", \"Furrer\", role = c(\"aut\"),\nemail = \"reinhard.furrer@math.uzh.ch\"),\nperson(\"John\", \"Paige\", role = c(\"aut\"),\nemail = \"paigejo@uw.edu\"),\nperson(\"Stephan\", \"Sain\", role = \"aut\",\nemail = \"sainsr2@gmail.com\"),\nperson(\"Florian\", \"Gerber\", role = \"aut\",\nemail = \"flora.fauna.gerber@gmail.com\"),\nperson(\"Matthew\", \"Iverson\", role = \"aut\",\nemail = \"miverson@mines.edu\"),\nperson(\"Rider\", \"Johnson\", role = \"aut\",\nemail = \"riderjohnson@mines.edu\")\n)", "Maintainer": "Douglas Nychka ", "Description": "For curve, surface and function fitting with an emphasis\non splines, spatial data, geostatistics, and spatial\nstatistics. The major methods include cubic, and thin plate\nsplines, Kriging, and compactly supported covariance functions\nfor large data sets. The splines and Kriging methods are\nsupported by functions that can determine the smoothing\nparameter (nugget and sill variance) and other covariance\nfunction parameters by cross validation and also by restricted\nmaximum likelihood. For Kriging there is an easy to use\nfunction that also estimates the correlation scale (range\nparameter). A major feature is that any covariance function\nimplemented in R and following a simple format can be used for\nspatial prediction. There are also many useful functions for\nplotting and working with spatial data as images. This package\nalso contains an implementation of sparse matrix methods for\nlarge spatial data sets and currently requires the sparse\nmatrix (spam) package. Use help(fields) to get started and for\nan overview. All graphics functions focus on using base R\ngraphics. The fields source code is deliberately commented and\nprovides useful explanations of numerical details as a\ncompanion to the manual pages. The commented source code can be\nviewed by expanding the source code version and looking in the\nR subdirectory. The reference for fields can be generated by\nthe citation function in R and has DOI .\nDevelopment of this package was supported in part by the\nNational Science Foundation Grant 1417857, the National Center\nfor Atmospheric Research, and Colorado School of Mines. See the\nFields URL for a vignette on using this package and some\nbackground on spatial statistics.", "License": "GPL (>= 2)", "URL": "https://github.com/dnychka/fieldsRPackage", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-06-07 06:13:43 UTC", "User": "root" }, "Author": "Douglas Nychka [aut, cre], Reinhard Furrer [aut], John Paige\n[aut], Stephan Sain [aut], Florian Gerber [aut], Matthew\nIverson [aut], Rider Johnson [aut]", "Repository": "https://dnychka.r-universe.dev", "Date/Publication": "2026-05-08 19:58:42 UTC", "RemoteUrl": "https://github.com/dnychka/fieldsrpackage", "RemoteRef": "HEAD", "RemoteSha": "6e9bbe0a86b56a0c2b18a37bff20144764429a4c", "RemoteSubdir": "fields", "MD5sum": "569d89b61ef6a9e376b0925c2cbe3ecb", "_user": "dnychka", "_type": "src", "_file": "fields_17.4.tar.gz", "_fileid": "2c9c5b5508bd30f2d1d4c19e1505536162a243b6fe19d21e54b8aa87e1e78992", "_filesize": 4861631, "_sha256": "2c9c5b5508bd30f2d1d4c19e1505536162a243b6fe19d21e54b8aa87e1e78992", "_created": "2026-06-07T06:13:43.000Z", "_published": "2026-06-07T06:23:27.421Z", "_distro": "noble", "_jobs": [ { "job": 79936648213, "time": 239, "config": "linux-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": "7461380344" }, { "job": 79936648172, "time": 271, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7461383809" }, { "job": 79936648220, "time": 233, "config": "linux-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7461379647" }, { "job": 79936648214, "time": 257, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7461382104" }, { "job": 79936648187, "time": 236, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7461379550" }, { "job": 79936648169, "time": 449, "config": "macos-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "7461404448" }, { "job": 79936648180, "time": 235, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7461379306" }, { "job": 79936648175, "time": 535, "config": "macos-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7461414581" }, { "job": 79936463137, "time": 191, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7461351317" }, { "job": 79936648184, "time": 92, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7461362265" }, { "job": 79936648167, "time": 378, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7461395819" }, { "job": 79936648177, "time": 291, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7461385877" }, { "job": 79936648170, "time": 364, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7461394353" } ], "_buildurl": "https://github.com/r-universe/dnychka/actions/runs/27084601119", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/dnychka/fieldsrpackage", "_commit": { "id": "6e9bbe0a86b56a0c2b18a37bff20144764429a4c", "author": "Douglas Nychka ", "committer": "Douglas Nychka ", "message": "first change for 17.5\n", "time": 1778270322 }, "_maintainer": { "name": "Douglas Nychka", "email": "douglasnychka@gmail.com", "login": "dnychka", "description": "I am data scientist interested in the application of statistical learning to interpret spatial and surface data in the environmental sciences and engineering. 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"page": "as.surface", "title": "Creates an \"surface\" object from grid values.", "topics": [ "as.surface" ] }, { "page": "BD", "title": "Data frame of the effect of buffer compositions on DNA strand displacement amplification. 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