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Maximum conditional likelihood estimation for the REST model with measurement error
DOI:10.1016/j.spl.2025.110581.png)
摘要
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.
Keyword:
Random encounter and staying time model
Population density
Conditional likelihood
Measurement error
期刊
S
IF:
0.7
论文数:
127
被引数:
0
机构
引用论文
Low population density of a tropical forest carnivore, Cryptoprocta ferox: implications for protected area management
Oryx
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Estimating animal density using camera traps without the need for individual recognition使用相机陷阱估计动物密度,而无需个人识别
Estimating animal density without individual recognition using information derivable exclusively from camera traps使用仅从相机陷阱中获取的信息来估计没有个体识别的动物密度
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