论文标题
统计推断在飞行临时模型下完成完整和不完整的移动轨迹
Statistical Inference for Complete and Incomplete Mobility Trajectories under the Flight-Pause Model
论文作者
论文摘要
我们为人类移动性制定了一个统计飞行临时模型，该模型由随机对象的集合（称为动议）代表，适用于手机跟踪（MPT）数据。我们在各种形式的缺失数据下开发了参数推理和轨迹推出的统计机制。我们表明，关于MPT缺失的数据机制的常见假设对于管理飞行临时模型的随机运动的机制无效，代表了研究不足的缺失数据现象。我们证明了丢失数据的后果以及我们在模拟和真实数据中提出的调整，概述了对MPT数据收集和设计的影响。
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.
