Authors@R: c(person("Aldo", "Gardini", email = "aldo.gardini2@unibo.it", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-2164-5815")),
person("Enrico", "Fabrizi", role = c("aut"), comment = c(ORCID = "0000-0003-2504-7043")),
person("Carlo", "Trivisano", role = c("aut"), comment = c(ORCID = "0000-0002-5991-4902")))
Author: Aldo Gardini [aut, cre] (<https://orcid.org/0000-0002-2164-5815>),

Imports: optimx, GeneralizedHyperbolic, gsl, coda, Rcpp (>= 0.12.17),

Author: Nicolas Polson, James G. Scott, and Jesse Windle
Description: The BayesLogit package does posterior simulation for
binary and multinomial logistic regression using the
Polya-Gamma latent variable technique. This method is fully
automatic, exact, and fast.  A routine to efficiently sample
from the Polya-Gamma class of distributions is included.

binomial and multinomial logistic regression using the

Description: The BayesLogit package does posterior simulation for binomial and
multinomial logistic regression using the Polya-Gamma latent variable
technique. This method is fully automatic, exact, and fast.  A routine to
efficiently sample from the Polya-Gamma class of distributions is included.

person("Jesse", "Windle", email = "jesse.windle@gmail.com",
person("James Joseph", "Balamuta", email = "balamut2@illinois.edu",
Description: Perform posterior simulation for binomial and
efficiently sample from the Polya-Gamma class of distributions is included
Maintainer: James Joseph Balamuta <balamut2@illinois.edu>

Description: Tools for sampling from the PolyaGamma distribution based on Polson, Scott, and Windle (2013) <doi:10.1080/01621459.2013.829001>.  Useful for logistic regression.

Title: Designing Bayesian Multi-Arm Multi-Stage Studies
Description: Calculating Bayesian sample sizes for multi-arm trials where several experimental treatments are compared to a common control, perhaps even at multiple stages.

Title: Bayesian Misclassified-Failure Survival Model
Authors@R: c(person(given = "Minnie M.",
Description: Contains a split population survival estimator that models the
misclassification probability of failure versus right-censored events.
The split population survival estimator is described in
Imports: MCMCpack, FastGP, stats, Rcpp (>= 1.0.3), coda, mvtnorm,
Packaged: 2019-12-19 03:31:08 UTC; Nicolás Schmidt