c(person("Gilles", "Kratzer", role = c("aut"),
email = "gilles.kratzer@gmail.com",
comment = c(ORCID = "0000-0002-5929-8935")),
person("Reinhard", "Furrer", role = c("ctb"),
email = "reinhard.furrer@math.uzh.ch",
comment = c(ORCID = "0000-0002-6319-2332")),
person("Annina","Cincera",role=c("cre"),
email = "annina.cincera@math.uzh.ch"))
abn, coda, gRbase, ggplot2, cowplot, ggpubr
Gilles Kratzer [aut] (<https://orcid.org/0000-0002-5929-8935>),
Reinhard Furrer [ctb] (<https://orcid.org/0000-0002-6319-2332>),
Annina Cincera [cre]

person("Joe", "Thorley", role = c("aut", "cre"), email = "joe@poissonconsulting.ca", comment = c(ORCID = "0000-0002-7683-4592"))
Generates derived parameter(s) from Monte Carlo Markov Chain (MCMC)
samples using R code. This allows Bayesian models to be fitted without the
inclusion of derived parameters which add unnecessary clutter and
slow model fitting. For more information on MCMC samples see
Brooks et al. (2011) <isbn:978-1-4200-7941-8>.

chk, abind, universals, extras, term, nlist, mcmcr (>= 0.3.0),
purrr

Generates derived parameter(s) from Monte Carlo
Markov Chain (MCMC) samples using R code. This allows Bayesian models
to be fitted without the inclusion of derived parameters which add
unnecessary clutter and slow model fitting. For more information on
MCMC samples see Brooks et al. (2011) <isbn:978-1-4200-7941-8>.
abind, chk, extras, mcmcr, nlist, purrr, universals

Generates derived parameter(s) from Monte Carlo Markov Chain
(MCMC) samples using R code. This allows Bayesian models to be fitted
without the inclusion of derived parameters which add unnecessary
clutter and slow model fitting. For more information on MCMC samples
see Brooks et al. (2011) <isbn:978-1-4200-7941-8>.

Ensemble Sampler for Affine-Invariant MCMC
c(person(given = "Hugo",
family = "Gruson",
role = c("cre", "aut", "cph"),
email = "hugo.gruson+R@normalesup.org",
comment = c(ORCID = "0000-0002-4094-1476")),
person(given = "Sanda",
family = "Dejanic",
role = c("aut", "cph")),
person(given = "Andreas",
family = "Scheidegger",
role = c("aut", "cph"),
comment = c(ORCID = "0000-0003-2575-2172")))
Provides ensemble samplers for
affine-invariant Monte Carlo Markov Chain, which allow a faster
convergence for badly scaled estimation problems. Two samplers are
proposed: the 'differential.evolution' sampler from ter Braak and
Vrugt (2008) <doi:10.1007/s11222-008-9104-9> and the 'stretch' sampler
from Goodman and Weare (2010) <doi:10.2140/camcos.2010.5.65>.
Hugo Gruson [cre, aut, cph] (<https://orcid.org/0000-0002-4094-1476>),
Sanda Dejanic [aut, cph],
Andreas Scheidegger [aut, cph]
(<https://orcid.org/0000-0003-2575-2172>)