https://github.com/lukasdsauer/baskoptr

Utility-based Optimization for Basket Trial Designs
https://github.com/lukasdsauer/baskoptr

basket-trials clinical-trials optimization utility-functions

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Utility-based Optimization for Basket Trial Designs

• Host: GitHub
• URL: https://github.com/lukasdsauer/baskoptr
• Owner: LukasDSauer
• License: other
• Created: 2023-01-30T09:11:36.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2025-09-19T09:10:27.000Z (10 months ago)
• Last Synced: 2025-09-19T11:30:12.540Z (10 months ago)
• Topics: basket-trials, clinical-trials, optimization, utility-functions
• Language: R
• Homepage:
• Size: 297 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE

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README

          
---

output: github_document

---

```{r, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  out.width = "100%"

)

```

# baskoptr 

[![Codecov test coverage](https://codecov.io/gh/LukasDSauer/baskoptr/graph/badge.svg)](https://app.codecov.io/gh/LukasDSauer/baskoptr)

[![R-CMD-check](https://github.com/LukasDSauer/baskoptr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/LukasDSauer/baskoptr/actions/workflows/R-CMD-check.yaml)

[![CRAN status](https://www.r-pkg.org/badges/version/baskoptr)](https://CRAN.R-project.org/package=baskoptr)

The goal of **baskoptr** is to supply 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.

## Installation

You can install the development version of baskoptr from [GitHub](https://github.com/) with:

``` r

# install.packages("pak")

pak::pak("LukasDSauer/baskoptr")

```

## Example

In the following example, we optimize Fujikawa et al.'s basket trial design

with respect to the experiment-wise power utility function using the simulated

annealing algorithm.

```{r example}

library(baskoptr)

# Optimizing a three-basket trial design using Fujikawa's beta-binomial

# sharing approach

design <- baskwrap::setup_fujikawa_x(k = 3, shape1 = 1, shape2 = 1,

                                     p0 = 0.2, backend = "exact")

detail_params <- list(p1 = c(0.5, 0.2, 0.2),

                      n = 20,

                      weight_fun = baskwrap::weights_jsd,

                      logbase = exp(1),

                      verbose = FALSE)

utility_params <- list(penalty = 1, thresh = 0.1)

opt_design_gen(design = design,

               utility = u_ewp,

               algorithm = optimizr::simann,

               detail_params = detail_params,

               utility_params = utility_params,

               algorithm_params = list(par = c(lambda = 0.99,

                                               epsilon = 2,

                                               tau = 0.5),

                                       lower = c(lambda = 0.001,

                                                 epsilon = 1,

                                                 tau = 0.001),

                                       upper = c(lambda = 0.999,

                                                 epsilon = 10,

                                                 tau = 0.999),

                                       control = list(maxit = 10,

                                                      temp = 10,

                                                      fnscale = -1,

                                                      REPORT = -1)))

```