We formulate a statistical flight-pause model for human mobility, represented by a collection of random objects, called motions, appropriate for mobile phone tracking (MPT) data. We develop the statistical machinery for parameter inference and trajectory imputation under various forms of missing data. We show that common assumptions about the missing data mechanism for MPT are not valid for the mechanism governing the random motions underlying the flight-pause model, representing an understudied missing data phenomenon. We demonstrate the consequences of missing data and our proposed adjustments in both simulations and real data, outlining implications for MPT data collection and design.

翻译：我们构建了一个用于人类移动性的统计飞行-暂停模型，该模型由一组称为“运动”的随机对象表示，适用于手机追踪数据。我们开发了在各类数据缺失情况下进行参数推断与轨迹插补的统计方法论。研究表明，针对手机追踪数据缺失机制的常见假设并不适用于飞行-暂停模型所支配的随机运动机制，这揭示了一种尚未充分研究的缺失数据现象。我们通过模拟实验和真实数据验证了数据缺失的后果及所提出的调整方案，并概述了对手机追踪数据收集与设计的启示。