Empirical Likelihood Inference for the Single-Species Occupancy Rate
- Resource Type
- Conference
- Authors
- Li, Huapeng; Liu, Yang
- Source
- 2023 IEEE/ACIS 23rd International Conference on Computer and Information Science (ICIS) Computer and Information Science (ICIS), 2023 IEEE/ACIS 23rd International Conference on. :200-205 Jun, 2023
- Subject
- Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineering Profession
Robotics and Control Systems
Surveys
Maximum likelihood estimation
Maximum likelihood detection
Information science
Simulation
Biological system modeling
Inference algorithms
- Language
Occupancy models have been popular in modeling imperfect detection in ecological surveys where the occupancy rate of a species is of most interest. In this paper, we incorporate the occupancy rate into likelihood and propose an empirical likelihood (EL) estimation approach associated with an EL ratio confidence interval. We show theoretically that the maximum EL estimator coincides with the maximum likelihood estimator and the EL ratio statistic of the occupancy rate asymptotically follows a chi-square distribution with one degree of freedom. An expectation-maximization (EM) algorithm is further developed from the computational perspective. Our simulation results indicate that compared with the Wald-type confidence interval, the coverage accuracy of the EL ratio confidence interval is generally more accurate, especially when the detection probability is small.