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We model two time and space scales discrete observations by using a uniquecontinuous diffusion process with time dependent coefficient. We define newparameters for the large scale model as functions of the small scaledistribution cumulants. We use the non - uniform distribution of theobservation time intervals to obtain consistent and unbiased estimators forthese parameters. Closed form expressions for migration proportions betweenspatial domains are derived as functions of these parameters. The models areapplied to estimate migration patterns from satellite tag data.

Estimating migration proportions from discretely observed continuous diffusion processes