2 citations · 3 across the 5 of their papers we have counts for
5 papers
Toward a Data Processing Pipeline for Mobile-Phone Tracking Data
Marcin Jurek, Catherine A. Calder, Corwin Zigler +2
As mobile phones become ubiquitous, high-frequency smartphone positioning data are increasingly being used by researchers studying the mobility patterns of individuals as they go a…
Statistical Inference for Complete and Incomplete Mobility Trajectories under the Flight-Pause Model
Marcin Jurek, Catherine A. Calder, Corwin Zigler
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. W…
Scalable Spatio-Temporal Smoothing via Hierarchical Sparse Cholesky Decomposition
Marcin Jurek, Matthias Katzfuss
We propose an approximation to the forward-filter-backward-sampler (FFBS) algorithm for large-scale spatio-temporal smoothing. FFBS is commonly used in Bayesian statistics when wor…
Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering
Marcin Jurek, Matthias Katzfuss
Spatial statistics often involves Cholesky decomposition of covariance matrices. To ensure scalability to high dimensions, several recent approximations have assumed a sparse Chole…
Multi-resolution filters for massive spatio-temporal data
Marcin Jurek, Matthias Katzfuss
Spatio-temporal data sets are rapidly growing in size. For example, environmental variables are measured with ever-higher resolution by increasing numbers of automated sensors moun…