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Table 1 Criteria for evaluating performance among model estimates for regional occupancy

From: Modeling regional occupancy of fishes using acoustic telemetry: a model comparison framework applied to lake trout

Test

Description

Interpretation

Mean weighted occupancy error (MOE)

Weighted mean of absolute difference between estimated occupancy for a region and the corresponding actual occupancy averaged across regions. Error for each region was weighted by the proportional use of each region

Larger error implies a less accurate occupancy model

Regional occupancy error (ROE)

Difference between estimated occupancy and actual occupancy for a given region

Positive values imply overestimates of regional occupancy; negative values imply underestimates of regional occupancy

Absolute regional occupancy error (aROE)

Absolute difference between estimated occupancy and actual occupancy for a given region

Larger error implies a less accurate regional occupancy model

Daily region assignment error

Percent incorrect model-based daily regional assignment for each simulation. When a simulated track or model indicated occupancy of more than one region on a given day, the region used most for each day was used for the comparison

Larger values imply model is not accurately estimating daily location of individual fish

Within-region occurrence error

Difference between the estimated number of distinct simulated tracks that occurred within a region based on movement model predictions and actual positions of all tracks

Positive values imply overestimates of distinct simulated tracks; negative values imply underestimates of distinct simulated tracks