Run other estimation and simulation software via the 'nlmixr2' (Fidler et al (2019)
  <doi:10.1002/psp4.12445>) interface including 'PKNCA', 'NONMEM' and 'Monolix'. While not required, you can
  get/install the 'lixoftConnectors' package in the 'Monolix' installation, as
  described at the following url
  <https://monolixsuite.slp-software.com/r-functions/2024R1/installation-and-initialization>. When
  'lixoftConnectors' is available, 'Monolix' can be run directly instead of setting up
  command line usage.

Provides a unified interface to interact with
    'docker' and 'singularity' containers.  You can execute a command
    inside a container, mount a volume or copy a file.

'BEAST2' (<https://www.beast2.org>) is a widely used
    Bayesian phylogenetic tool, that uses DNA/RNA/protein data
    and many model priors to create a posterior of jointly estimated 
    phylogenies and parameters.
    'BEAST2' is commonly accompanied by 'BEAUti 2', 'Tracer' and 'DensiTree'.
    'babette' provides for an alternative workflow of using 
    all these tools separately. This allows doing complex Bayesian
    phylogenetics easily and reproducibly from 'R'.

US baby names provided by the SSA. This package contains all
    names used for at least 5 children of either sex.

Israeli baby names provided by Israel's Central Bureau of Statistics. The package contains only names used for at least 5 children in at least one gender and sector ("Jewish", "Muslim", "Christian", "Druze" and "Other"). Data was downloaded from: <https://www.cbs.gov.il/he/publications/LochutTlushim/2020/%D7%A9%D7%9E%D7%95%D7%AA-%D7%A4%D7%A8%D7%98%D7%99%D7%99%D7%9D.xlsx>.

The BACCO bundle of packages is replaced by the BACCO
 package, which provides a vignette that illustrates the constituent
 packages (emulator, approximator, calibrator) in use.

Implements the Bayesian Augmented Control (BAC, a.k.a. Bayesian historical data borrowing) method under clinical trial setting by calling 'Just Another Gibbs Sampler' ('JAGS') software. In addition, the 'BACCT' package evaluates user-specified decision rules by computing the type-I error/power, or probability of correct go/no-go decision at interim look. The evaluation can be presented numerically or graphically. Users need to have 'JAGS' 4.0.0 or newer installed due to a compatibility issue with 'rjags' package. Currently, the package implements the BAC method for binary outcome only. Support for continuous and survival endpoints will be added in future releases. We would like to thank AbbVie's Statistical Innovation group and Clinical Statistics group for their support in developing the 'BACCT' package.