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The prior class\nprovides flexibility in capturing a wide array of prior beliefs\n(right-skewed and left-skewed) as modulated by a parameter that\nis bounded in (0,1). The generated samples can be used to\nsimulate the prior and posterior predictive distributions. More\ndetails can be found in Cahoy and Sedransk (2019)\n. The package can also be used\nas a teaching demo for introductory Bayesian courses.", "License": "GPL (>= 3)", "Encoding": "UTF-8", "RoxygenNote": "7.2.1", "Repository": "https://dcahoy.r-universe.dev", "Date/Publication": "2022-08-25 02:38:29 UTC", "RemoteUrl": "https://github.com/dcahoy/invstableprior", "RemoteRef": "HEAD", "RemoteSha": "6e7e9a1a8e784b6c0833f2e9cece5b575ad32493", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-18 06:05:46 UTC", "User": "root" }, "Author": "Dexter Cahoy [aut, cre],\nJoseph Sedransk [aut]", "Maintainer": "Dexter Cahoy ", "MD5sum": "db59667277989a31375837df9fd84979", "_user": "dcahoy", "_type": "src", "_file": "InvStablePrior_0.1.0.tar.gz", "_fileid": "f8d2c4c7284872fc981d61c757320b5475a8a6f346bb771aadbb4d01478aebab", "_filesize": 104624, "_sha256": "f8d2c4c7284872fc981d61c757320b5475a8a6f346bb771aadbb4d01478aebab", "_created": "2026-05-18T06:05:46.000Z", "_published": "2026-06-02T16:49:00.306Z", "_distro": "noble", "_jobs": [ { "job": 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