Determines effective sample size of a parametric prior distribution
in Bayesian models. For a web-based Shiny application related to this package, see <https://implement.shinyapps.io/bayesess/>.

person("Rémi", "Piatek", email = "remi.piatek@econ.ku.dk",
role = c("aut", "cre"))
Collection of procedures to perform Bayesian analysis on a variety
of factor models. Currently, it includes: Bayesian Exploratory Factor
Analysis (befa), an approach to dedicated factor analysis with stochastic
search on the structure of the factor loading matrix. The number of latent
factors, as well as the allocation of the manifest variables to the factors,
are not fixed a priori but determined during MCMC sampling.
More approaches will be included in future releases of this package.

checkmate (>= 1.8.0), coda, ggplot2 (>= 2.1.0), gridExtra,
plyr (>= 1.8.0)

person("R\u00e9mi", "Piatek",
role = c("aut", "cre"),
email = "remi.piatek@econ.ku.dk",
comment = c(ORCID = "0000-0002-3474-1304"))

person("R\u00e9mi", "Piatek",
role = c("aut", "cre"),
email = "remi.piatek@gmail.com",
comment = c(ORCID = "0000-0002-3474-1304"))

person(
given = "Rémi",
family = "Piatek",
role = c("aut", "cre"),
email = "remi.piatek@gmail.com",
comment = c(ORCID = "0000-0002-3474-1304"))
Collection of procedures to perform Bayesian analysis on a variety
of factor models. Currently, it includes: "Bayesian Exploratory Factor
Analysis" (befa) from G. Conti, S. Frühwirth-Schnatter, J.J. Heckman,
R. Piatek (2014) <doi:10.1016/j.jeconom.2014.06.008>, an approach to
dedicated factor analysis with stochastic search on the structure of the
factor loading matrix. The number of latent factors, as well as the
allocation of the manifest variables to the factors, are not fixed a priori
but determined during MCMC sampling.

Computation of Bayes factors for simple psychological designs
The BayesFactor package is a suite of functions for
computing various Bayes factors for simple designs, including
the one- and two-sample designs, one-way designs, general ANOVA
designs, and linear regression.