Imports: SPOT, checkmate, curl, data.table, dplyr, ggplot2, golem,
igraph, lubridate, markovchain, methods, padr, parallel, rvest,
scales, simmer, slider, testthat, plyr, xml2
Suggests: batchtools, knitr, rpart, rpart.plot, simmer.plot, stringr,

Suggests: batchtools, knitr, rmarkdown, rpart, rpart.plot, simmer.plot,

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

person("Hadley", "Wickham", , "hadley@rstudio.com", c("aut", "cre")),

person("Aviezer", "Lifshitz", , "aviezer.lifshitz@weizmann.ac.il", role = c("aut", "cre"))
Description: 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>.
Suggests: testthat (>= 3.0.0), dplyr, knitr, rmarkdown

Title: Bayesian Classification and Information Sharing (BaCIS) Tool for
the Design of Multi-Group Phase II Clinical Trials
Description: Provides the design of multi-group phase
II clinical trials with binary outcomes using the hierarchical Bayesian
classification and information sharing (BaCIS) model. Subgroups are classified
into two clusters on the basis of their outcomes mimicking the hypothesis
testing framework. Subsequently, information sharing takes place within
subgroups in the same cluster, rather than across all subgroups. This method can
be applied to the design and analysis of multi-group clinical trials with binary

outcomes. Reference: Nan Chen and J. Jack Lee (2019) <doi:10.1002/bimj.201700275>.

Title: Learning Causal Cyclic Graphs from Unknown Shift Interventions
Imports: jointDiag, clue, pcalg, igraph, matrixcalc, reshape2
Description: Code for 'backShift', an algorithm to estimate the connectivity
matrix of a directed (possibly cyclic) graph with hidden variables. The
underlying system is required to be linear and we assume that observations
under different shift interventions are available. For more details,