A semi-parametric maximum-likelihood analysis of measurement error in population size estimation
针对捕获-再捕获研究中协变量测量误差导致偏差的问题，提出非参数测量误差模型，用EM算法估计参数，结合Horvitz-Thompson估计量提高种群规模估计的准确性和可靠性。
Abstract This work addresses the challenge of measurement errors in capture–recapture (CR) studies with covariates. These errors can introduce bias and undermine inference quality. To address this issue, we introduce a nonparametric measurement error model tailored to the ‘repeated counts’ setting, employing EM-type algorithms for parameter estimation. We use the Horvitz–Thompson estimator for population size estimates. Rigorous simulations, covering varying degrees of measurement error reliability, confirm our approach’s effectiveness. Applied to benchmark datasets, it consistently provides more accurate point estimates and robust uncertainty quantification, enhancing the reliability of CR analyses.