Bayesian continuous reassessment method (CRM) designs for Phase
I dose-finding trials.

Bayesian continual reassessment method (CRM) designs for Phase I
dose-finding trials.
This package implements a wide variety of one and two-parameter Bayesian CRM designs. The program can run interactively, allowing the user to enter outcomes after each cohort has been recruited, or via simulation to assess operating characteristics.

Bayesian Continual Reassessment Method for Phase I
Dose-Escalation Trials
Implements a wide variety of one and two-parameter Bayesian CRM designs. The program can run interactively, allowing the user to enter outcomes after each cohort has been recruited, or via simulation to assess operating characteristics.

Implements a wide variety of one and two-parameter Bayesian CRM
designs. The program can run interactively, allowing the user to enter outcomes
after each cohort has been recruited, or via simulation to assess operating
characteristics.

c(
person("Michael", "Sweeting", email="michael.sweeting@leicester.ac.uk", role= "aut"),
person("Graham", "Wheeler", email="graham.wheeler@ucl.ac.uk", role=c("aut", "cre"))
)
Implements a wide variety of one- and two-parameter Bayesian CRM
designs. The program can run interactively, allowing the user to enter outcomes
after each cohort has been recruited, or via simulation to assess operating
characteristics.
graphics, stats, mvtnorm, rlang, ggplot2 (>= 1.0.1), grid,
BRugs, R2WinBUGS, rjags, knitr
Michael Sweeting [aut],
Graham Wheeler [aut, cre]

graphics, stats, mvtnorm, rlang, ggplot2 (>= 1.0.1), grid,
knitr

Implements a wide variety of one- and two-parameter Bayesian CRM
designs. The program can run interactively, allowing the user to enter outcomes
after each cohort has been recruited, or via simulation to assess operating
characteristics. See Sweeting et al. (2013): <doi:10.18637/jss.v054.i13>.

c(
person("Jeroen", "Ooms", , "jeroen.ooms@stat.ucla.edu", role = c("cre", "aut")),
person("Damien", "Miller", role = "cph"),
person("Niels", "Provos", role = "cph")
)
An R interface to the 'OpenBSD Blowfish' password hashing algorithm,
as described in "A Future-Adaptable Password Scheme" by 'Niels Provos'. The
implementation is derived from the 'py-bcrypt' module for Python which is a
wrapper for the 'OpenBSD' implementation.
Jeroen Ooms [cre, aut],
Damien Miller [cph],
Niels Provos [cph]