Correcting home-range models for observation bias
作者： JON S. HORNE , EDWARD O. GARTON , KIMBERLY A. SAGER-FRADKIN
DOI: 10.2193/2005-678
关键词:
摘要: Home-range models implicitly assume equal observation rates across the study area. Because this assumption is frequently violated, we describe methods for correcting home-range bias. We suggest corrections 3 general types of including those which parameters are estimated using least-squares theory, utilizing maximum likelihood parameter estimation, and based on kernel smoothing techniques. When applied to mule deer (Odocoileus hemionus) location data, found that uncorrected estimates utilization distribution were biased low by as much 18.4% high 19.2% when compared corrected estimates. magnitude bias related several factors, future research should determine relative influence each these factors
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