Bidirectional imputation of spatial GPS trajectories with missingness using sparse online Gaussian Process.

ABSTRACT:

Objective

We propose a bidirectional GPS imputation method that can recover real-world mobility trajectories even when a substantial proportion of the data are missing. The time complexity of our online method is linear in the sample size, and it provides accurate estimates on daily or hourly summary statistics such as time spent at home and distance traveled.

Materials and methods

To preserve a smartphone's battery, GPS may be sampled only for a small portion of time, frequently <10%, which leads to a substantial missing data problem. We developed an algorithm that simulates an individual's trajectory based on observed GPS location traces using sparse online Gaussian Process to addresses the high computational complexity of the existing method. The method also retains the s

SUBMITTER: Liu G 

PROVIDER: S-EPMC8324229 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature