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  "Title": "Estimating the Degrees of Freedom of the Student's\nt-Distribution under a Bayesian Framework",
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  "Authors@R": "c(person(given = \"Somjit\",\nfamily = \"Roy\",\nemail = \"sroy_123@tamu.edu\",\nrole = c(\"aut\", \"cre\")),\nperson(given = c(\"Se\", \"Yoon\"),\nfamily = \"Lee\",\nemail = \"seyoonlee.stat.math@gmail.com\",\nrole = c(\"aut\", \"ctb\")))",
  "Description": "A Bayesian framework to estimate the Student's\nt-distribution's degrees of freedom is developed. Markov Chain\nMonte Carlo sampling routines are developed as in\n<doi:10.3390/axioms11090462> to sample from the posterior\ndistribution of the degrees of freedom. A random walk\nMetropolis algorithm is used for sampling when Jeffrey's and\nGamma priors are endowed upon the degrees of freedom. In\naddition, the Metropolis-adjusted Langevin algorithm for\nsampling is used under the Jeffrey's prior specification. The\nLog-normal prior over the degrees of freedom is posed as a\nviable choice with comparable performance in simulations and\nreal-data application, against other prior choices, where an\nElliptical Slice Sampler is used to sample from the concerned\nposterior.",
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  "Date/Publication": "2025-01-09 05:00:11 UTC",
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