Fig. 6
From: Accounting for location uncertainty in azimuthal telemetry data improves ecological inference
Simulation comparing regression coefficient point estimates from a resource selection function analysis that incorporates location uncertainty (i.e., azimuthal telemetry model (ATM)), locations estimated using Lenth’s (1981) maximum likelihood estimate and ignores location uncertainty, and when true spatial location values are known with complete certainty. Coefficient point estimates correspond to a continuous and categorical variable (γ1,γ2, respectively) under low to high autocorrelation. Thick lines are 50% credible intervals and thin lines are 95% credible intervals. The top row (a, b) correspond to using covariates simulated at a high spatial resolution (25 m) and the bottom row (c, d) correspond to using low spatial resolution covariates (100 m). The columns differ in the size of the simulated dataset: 50 or 200 locations