Software for Data-Based Stochastic Programming Using Bootstrap Estimation
该软件仅使用样本数据，通过自助法和装袋法得到一致的样本平均解和最优性间隙的置信区间估计，无需知道数据背后的真实分布。
We describe software for stochastic programming that uses only sampled data to obtain both a consistent sample-average solution and a consistent estimate of confidence intervals for the optimality gap using bootstrap and bagging. The underlying distribution whence the samples come is not required. History: Accepted by Ted Ralphs, Area Editor for Software Tools. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0253 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2022.0253 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .