This package is considered a duplicate. The official version of this package is found at:https://madsyair.r-universe.dev/neojags

Package: neojags 0.1.7

Achmad Syahrul Choir

neojags: Neo-Normal Distributions Family for Markov Chain Monte Carlo (MCMC) Models in 'JAGS'

A 'JAGS' extension module provides neo-normal distributions family including MSNBurr, MSNBurr-IIa, GMSNBurr, Lunetta Exponential Power, Fernandez-Steel Skew t, Fernandez-Steel Skew Normal, Fernandez-Osiewalski-Steel Skew Exponential Power, Jones Skew Exponential Power. References: Choir, A. S. (2020). "The New Neo-Normal Distributions and Their Properties".Unpublished Dissertation. Denwood, M.J. (2016) <doi:10.18637/jss.v071.i09>. Fernandez, C., Osiewalski, J., & Steel, M. F. (1995) <doi:10.1080/01621459.1995.10476637>. Fernandez, C., & Steel, M. F. (1998) <doi:10.1080/01621459.1998.10474117>. Iriawan, N. (2000). "Computationally Intensive Approaches to Inference in NeoNormal Linear Models".Unpublished Dissertation. Mineo, A., & Ruggieri, M. (2005) <doi:10.18637/jss.v012.i04>. Rigby, R. A., & Stasinopoulos, D. M. (2005) <doi:10.1111/j.1467-9876.2005.00510.x>. Lunetta, G. (1963). "Di una Generalizzazione dello Schema della Curva Normale". Rigby, R. A., Stasinopoulos, M. D., Heller, G. Z., & Bastiani, F. D. (2019) <doi:10.1201/9780429298547>.

Authors:Achmad Syahrul Choir [aut, cre], Resi Ramadani [aut], Nur Iriawan [aut], S Sifa'ul Khusna Malikhatul Mutmainah [ctb], Matthew Denwood [cph], Martyn Plummer [cph]

neojags_0.1.7.tar.gz
neojags_0.1.7.tar.gz(r-4.7-arm64)neojags_0.1.7.tar.gz(r-4.7-x86_64)neojags_0.1.7.tar.gz(r-4.6-arm64)neojags_0.1.7.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
neojags/json (API)

# Install 'neojags' in R:

install.packages('neojags', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/madsyair/neojags/issues

Uses libs:

jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
c++– GNU Standard C++ Library v3

On CRAN:

jags cpp

2.70 score 3 scripts 200 downloads 4 exports 4 dependencies

Last updated from:c8941fb2a7. Checks:4 NOTE, 1 OK, 1 FAIL. Indexed: no.

Target	Result	Time
linux-devel-arm64	NOTE	132
linux-devel-x86_64	NOTE	136
source / vignettes	OK	212
linux-release-arm64	NOTE	164
linux-release-x86_64	NOTE	145
wasm-release	FAIL	114