{ "_id": "6a103badacfb0bcc41c9b991", "Package": "tmvmixnorm", "Type": "Package", "Title": "Sampling from Truncated Multivariate Normal and t Distributions", "Version": "1.2.0", "Authors@R": "c(person(\"Ting Fung\", \"Ma\", email = \"tingfung@mailbox.sc.edu\", role = c(\"cre\", \"aut\")),\nperson(\"Sujit K.\", \"Ghosh\", email = \"sujit_ghosh@ncsu.edu\", role = \"aut\"),\nperson(\"Yifang\", \"Li\", role = \"aut\"))", "Maintainer": "Ting Fung Ma ", "Description": "Efficient sampling of truncated multivariate (scale)\nmixtures of normals under linear inequality constraints is\nnontrivial due to the analytically intractable normalizing\nconstant. Meanwhile, traditional methods may subject to\nnumerical issues, especially when the dimension is high and\ndependence is strong. Algorithms proposed by Li and Ghosh\n(2015) are adopted for\novercoming difficulties in simulating truncated distributions.\nEfficient rejection sampling for simulating truncated\nunivariate normal distribution is included in the package,\nwhich shows superiority in terms of acceptance rate and\nnumerical stability compared to existing methods and R\npackages. An efficient function for sampling from truncated\nmultivariate normal distribution subject to convex polytope\nrestriction regions based on Gibbs sampler for conditional\ntruncated univariate distribution is provided. By extending the\nsampling method, a function for sampling truncated multivariate\nStudent's t distribution is also developed. Moreover, the\nproposed method and computation remain valid for high\ndimensional and strong dependence scenarios. Empirical results\nin Li and Ghosh (2015) \nillustrated the superior performance in terms of various\ncriteria (e.g. mixing and integrated auto-correlation time).", "License": "GPL-2", "Encoding": "UTF-8", "RoxygenNote": "7.3.3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-11 10:43:37 UTC", "User": "root" }, "Author": "Ting Fung Ma [cre, aut], Sujit K. Ghosh [aut], Yifang Li [aut]", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2026-05-11 08:40:13 UTC", "RemoteUrl": "https://github.com/cran/tmvmixnorm", "RemoteRef": "HEAD", "RemoteSha": "47b3718573116031a8700e5905a49a6f938d4bd0", "MD5sum": "f58e109f9909ada9340775456662bfbc", "_user": "cran", "_type": "src", "_file": "tmvmixnorm_1.2.0.tar.gz", "_fileid": "ef9ce9490ed11a6bb82a1c68bb10ef469f4a1cd079e02407efc7d827a9b43e4c", "_filesize": 107698, "_sha256": "ef9ce9490ed11a6bb82a1c68bb10ef469f4a1cd079e02407efc7d827a9b43e4c", "_created": "2026-05-11T10:43:37.000Z", "_published": "2026-05-22T11:19:09.415Z", "_distro": "noble", "_jobs": [ { "job": 77369140479, "time": 114, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "6916411174" }, { "job": 77369140703, "time": 96, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "6916407547" }, { "job": 77369140187, "time": 155, "config": "source", "r": "4.6.0", "check": "OK", 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sampling", "topics": [ "norm_rej" ] }, { "page": "ptuvn", "title": "Distribution function of truncated univariate normal distribution", "topics": [ "ptuvn" ] }, { "page": "rtmvn", "title": "Random number generation for truncated multivariate normal distribution subject to linear inequality constraints", "topics": [ "rtmvn" ] }, { "page": "rtmvt", "title": "Random number generation for truncated multivariate Student's t distribution subject to linear inequality constraints", "topics": [ "rtmvt" ] }, { "page": "rtuvn", "title": "Random number generation for truncated univariate normal distribution", "topics": [ "rtuvn" ] }, { "page": "unif_acc", "title": "Acceptance rate of uniform rejection sampling", "topics": [ "unif_acc" ] }, { "page": "unif_rej", "title": "Uniform rejection sampling", "topics": [ "unif_rej" ] } ], "_rundeps": [ "MASS" ], "_score": 2.3692158574101425, "_indexed": true, "_nocasepkg": "tmvmixnorm", "_universes": [ "cran", "ralphma1203" ], "_binaries": [ { "r": "4.7.0", 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