TY - GEN
T1 - Combining spatial and telemetric features for learning animal movement models
AU - Kapicioglu, Berk
AU - Schapire, Robert E.
AU - Wikelski, Martin
AU - Broderick, Tamara
PY - 2010/12/1
Y1 - 2010/12/1
N2 - We introduce a new graphical model for tracking radio-tagged animals and learning their movement patterns. The model provides a principled way to combine radio telemetry data with an arbitrary set of userdefined, spatial features. We describe an efficient stochastic gradient algorithm for fitting model parameters to data and demonstrate its effectiveness via asymptotic analysis and synthetic experiments. We also apply our model to real datasets, and show that it outperforms the most popular radio telemetry software package used in ecology. We conclude that integration of different data sources under a single statistical framework, coupled with appropriate parameter and state estimation procedures, produces both accurate location estimates and an interpretable statistical model of animal movement.
AB - We introduce a new graphical model for tracking radio-tagged animals and learning their movement patterns. The model provides a principled way to combine radio telemetry data with an arbitrary set of userdefined, spatial features. We describe an efficient stochastic gradient algorithm for fitting model parameters to data and demonstrate its effectiveness via asymptotic analysis and synthetic experiments. We also apply our model to real datasets, and show that it outperforms the most popular radio telemetry software package used in ecology. We conclude that integration of different data sources under a single statistical framework, coupled with appropriate parameter and state estimation procedures, produces both accurate location estimates and an interpretable statistical model of animal movement.
UR - http://www.scopus.com/inward/record.url?scp=80053163912&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:80053163912
SN - 9780974903965
T3 - Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010
SP - 260
EP - 267
BT - Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010
T2 - 26th Conference on Uncertainty in Artificial Intelligence, UAI 2010
Y2 - 8 July 2010 through 11 July 2010
ER -