Bayesian Melding of the Dead-Reckoned Path and GPS Measurements for an   Accurate and High-Resolution Path of Marine Mammals
  With the recent advances in electrical engineering, devices attached to free-ranging marine mammals today can collect oceanographic data in remarkable high spatial-temporal resolution. However, those data cannot be fully utilized without a matching high-resolution and accurate path of the animal, which is currently missing in this field. In this paper, we develop a Bayesian melding approach based on a Brownian Bridge process to combine the fine-resolution but seriously biased Dead-Reckoned path and the precise but sparse GPS measurements, which results in an accurate and high-resolution estimated path together with credible bands as quantified uncertainty statements. We also exploit the properties of underlying processes and some approximations to the likelihood to dramatically reduce the computational burden of handling those big high resolution data sets. 
Yang Liu, Brian C. Battaile, James V. Zidek and Andrew W. Trites
stat.AP