The \pkg{pintervals} package aims to provide a unified framework for constructing prediction intervals and calibrating predictions in a model-agnostic setting using set-aside calibration data. It comprises routines to construct conformal as well as parametric and bootstrapped prediction intervals from any model that outputs point predictions. Several R packages and functions already exist for constructing prediction intervals, but they often focus on specific modeling frameworks or types of predictions, or require manual customization for different models or applications. By providing a consistent interface for a variety of prediction interval construction approaches (all model-agnostic), \pkg{pintervals} allows researchers to apply and compare them across different modeling frameworks and applications.

翻译：\pkg{pintervals}软件包旨在提供一个统一框架，用于在模型无关的设置下利用预留校准数据构建预测区间并校准预测。该软件包包含从任何输出点预测的模型中构建符合预测区间、参数预测区间以及自助法预测区间的程序。目前已有多个R软件包和函数用于构建预测区间，但它们通常专注于特定的建模框架或预测类型，或者需要针对不同模型或应用进行手动定制。通过为多种预测区间构建方法（均为模型无关）提供一致的接口，\pkg{pintervals}使研究人员能够在不同的建模框架和应用中应用并比较这些方法。