AI 中文总结
本文提出适用于个体出行数据的microPURC估计量，采用嵌套不动点算法，经模拟数据验证统计性质，并用真实大数据集实践，完善扰动效用路径选择模型的估计方法。
AI 中文摘要
我们提供一种适用于个体出行层级数据的扰动效用路径选择（PURC）模型的估计量。该估计量为嵌套不动点算法，结合上层偏差校正线性回归问题与下层个体层级扰动效用最大化问题。我们建立microPURC估计量的统计性质，并通过模拟数据实验验证结果，最后用大型真实世界数据集在实践中展示该估计量。
英文摘要
We provide an estimator for the perturbed utility route choice (PURC) model that works with data at the level of individual trips. The estimator is a nested fixed-point algorithm that combines an upper bias-corrected linear regression problem with a lower individual-level perturbed utility maximization problem. We establish the statistical properties of the microPURC estimator and confirm these results with an experiment using simulated data. Finally, we demonstrate the estimator in practice using a large real-world dataset.
