  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.
