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Maximum conditional likelihood estimation for the REST model with measurement error
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DOI：10.1016/j.spl.2025.110581.png)
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Abstract
En 中文
We propose a maximum conditional likelihood estimation approach for the random encounter and staying time model, incorporating simulation-extrapolation to correct for biases arising from measurement error. The effectiveness of proposed methods is demonstrated via simulations and field data.
Keywords:
Random encounter and staying time model
Population density
Conditional likelihood
Measurement error
Journal
S
IF:
0.7
Papers:
121
Citations:
0