This package is considered a duplicate. The official version of this package is found at:https://lukasdsauer.r-universe.dev/baskoptr

Package: baskoptr 1.0.4

Lukas D Sauer

baskoptr: Utility-Based Optimization for Basket Trial Designs

A unified framework for optimizing basket trial designs. To this end, the package supplies several utility functions and also a function for executing optimization algorithms on basket trial designs. The considered utility functions are discussed in Sauer et al. (2025) <doi:10.1371/journal.pone.0323097>.

Authors:Lukas D Sauer [aut, cre]

baskoptr_1.0.4.tar.gz
baskoptr_1.0.4.tar.gz(r-4.7-any)baskoptr_1.0.4.tar.gz(r-4.6-any)
baskoptr_1.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
baskoptr/json (API)

# Install 'baskoptr' in R:

install.packages('baskoptr', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/lukasdsauer/baskoptr/issues

Uses libs:

jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
c++– GNU Standard C++ Library v3

On CRAN:

jags cpp

1.70 score 3 scripts 146 downloads 11 exports 47 dependencies

Last updated from:10a010f543. Checks:4 OK. Indexed: no.

Target	Result	Time
linux-devel-x86_64	OK	322
source / vignettes	OK	190
linux-release-x86_64	OK	309
wasm-release	OK	119

Exports:epsilon_extreme get_p1s get_scenarios opt_design_gen tau_extreme u_2ewp u_2pow u_avg u_bnd u_ecd u_ewp

Dependencies:arrangements backports baskexact basksim baskwrap bhmbasket checkmate cli coda codetools cpp11 digest doFuture doRNG extraDistr farver foreach future future.apply ggplot2 globals glue gmp gtable HDInterval isoband iterators labeling lattice lifecycle listenv magrittr parallelly progressr purrr R6 RColorBrewer Rcpp RcppArmadillo rjags rlang rngtools S7 scales vctrs viridisLite withr

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Readme and manuals

Help Manual

Help page	Topics
Internal helper function: Append and set elements of a details list	append_details set_details
Extreme borrowing cutoffs for borrowing in Fujikawa's design	epsilon_extreme tau_extreme
Internal helper function: Get details for two response scenarios	get_details_for_two_scenarios
Generate an array of possible outcome scenarios	get_p1s
Generate a scenario of possible outcomes	get_scenarios
Internal helper function: Decide whether to record a trace and what path to use	get_trace_info
Internal helper function: Input validation for p1	io_val_p1
Optimize a Basket Trial Design	opt_design_gen
List of parameters used across the package	params_main
List of parameters used for functions calling utility functions	params_utility_caller
Utility functions: Two-level power-error combination functions	u_2ewp u_2pow
Utility function: Scenario-averaged utility function	u_avg
Utility function with boundaries on the parameters	u_bnd
Utility functions: Discontinuous power/ECD functions with type-I error penalty	u_ecd u_ewp

Package: baskoptr 1.0.4

baskoptr: Utility-Based Optimization for Basket Trial Designs

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)