c(person("Ben Bolker",role=c("aut","cre"),
email="bolker@mcmaster.ca"),
person("Hans","Skaug",role="aut"),
person("Jeff","Laake",role="aut"))
Ben Bolker [aut, cre],
Hans Skaug [aut],
Jeff Laake [aut]

bbmle, lme4, ggplot2 (>= 3.4.0), testthat, knitr

A series of functions to call AD Model Builder (i.e., compile and run models) from within R, read the results back into R as "admb" objects, and provide standard accessors (i.e. coef(), vcov(), etc.)

R2jags: A Package for Running jags from R
Yu-Sung Su <ys463@columbia.edu>,
Masanao Yajima <yajima@stat.columbia.edu>,
methods, R(>= 2.7.0), coda, R2WinBUGS, rjags(>= 1.0.3)

methods, R(>= 2.7.0), coda, R2WinBUGS, rjags(>= 1.0.3-7)

methods, R(>= 2.7.0), coda, R2WinBUGS, rjags(>= 1.0.3-8)

Yu-Sung Su <ys463@columbia.edu>, Masanao Yajima
<yajima@stat.columbia.edu>,

Yu-Sung Su <suyusung@tsinghua.edu.cn>, Masanao Yajima
<yajima@stat.columbia.edu>,

methods, R (>= 2.14.0), coda (>= 0.13), R2WinBUGS, rjags (>=
3-3), parallel

methods, R (>= 2.14.0), coda (>= 0.13), R2WinBUGS, rjags (>=
3-3), abind, parallel

Yu-Sung Su <suyusung@tsinghua.edu.cn>, Masanao Yajima
<yajima@stat.ucla.edu>,

Yu-Sung Su <suyusung@tsinghua.edu.cn>,
Masanao Yajima <yajima@stat.ucla.edu>,

abind, coda (>= 0.13), methods, R2WinBUGS, parallel

Using this package to call 'JAGS' from R.

Providing wrapper functions to implement Bayesian analysis in JAGS.  Some major features include monitoring convergence of a MCMC model using Rubin and Gelman Rhat statistics, automatically running a MCMC model till it converges, and implementing parallel processing of a MCMC model for multiple chains.

abind, coda (>= 0.13), graphics, grDevices, methods,
R2WinBUGS, parallel, stats, utils

Yu-Sung Su <suyusung@tsinghua.edu.cn>,
Masanao Yajima <yajima@bu.edu>,

Two Sample Problem Routines using Permutation
person("Wolfgang", "Rolke", , "wolfgang.rolke@upr.edu", role = c("aut", "cre"),
comment = c(ORCID = "0000-0002-3514-726X"))
The routine twosample_test() in this package runs the
two sample test using various test statistic. The p values are
found via permutation. The routine twosample_power() allows the
calculation of the power in various cases, and plot_power()
draws the corresponding power graphs.
Rcpp, parallel, shiny, ggplot2, microbenchmark
Wolfgang Rolke [aut, cre] (<https://orcid.org/0000-0002-3514-726X>)