Package: bayesestdft
Title: Estimating the Degrees of Freedom of the Student's
        t-Distribution under a Bayesian Framework
Version: 1.0.0
Authors@R: 
    c(person(given = "Somjit", 
    family = "Roy",
    email = "sroy_123@tamu.edu", 
    role = c("aut", "cre")),
    person(given = c("Se", "Yoon"), 
    family = "Lee",
    email = "seyoonlee.stat.math@gmail.com", 
    role = c("aut", "ctb")))
Description: A Bayesian framework to estimate the Student's
        t-distribution's degrees of freedom is developed. Markov Chain
        Monte Carlo sampling routines are developed as in
        <doi:10.3390/axioms11090462> to sample from the posterior
        distribution of the degrees of freedom. A random walk
        Metropolis algorithm is used for sampling when Jeffrey's and
        Gamma priors are endowed upon the degrees of freedom. In
        addition, the Metropolis-adjusted Langevin algorithm for
        sampling is used under the Jeffrey's prior specification. The
        Log-normal prior over the degrees of freedom is posed as a
        viable choice with comparable performance in simulations and
        real-data application, against other prior choices, where an
        Elliptical Slice Sampler is used to sample from the concerned
        posterior.
License: MIT + file LICENSE
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
URL: https://github.com/Roy-SR-007/bayesestdft
BugReports: https://github.com/Roy-SR-007/bayesestdft/issues
Imports: numDeriv, dplyr
Depends: R (>= 4.0.4)
LazyData: true
Repository: https://roy-sr-007.r-universe.dev
Date/Publication: 2025-01-09 05:00:11 UTC
RemoteUrl: https://github.com/roy-sr-007/bayesestdft
RemoteRef: HEAD
RemoteSha: e72ac816f1b199a70e9f9b0d4e15a65b13e7ecaf
NeedsCompilation: no
Packaged: 2026-07-10 08:44:35 UTC; root
Author: Somjit Roy [aut, cre],
  Se Yoon Lee [aut, ctb]
Maintainer: Somjit Roy <sroy_123@tamu.edu>