On the robustness of the Chao's estimator with covariate information and measurement error for population size estimation

This research presents a contribution to the field of capture-recapture count data analysis, focusing on the robustness of Chao's estimator to measurement error when covariate information is incorporated. In particular, Chao's lower bound under exponential heterogeneity is extended to the covariate setting using a conditional likelihood approach. The findings, based on artificial examples, emphasize the resilience of Chao's estimator in the presence of measurement error. This research enhances our understanding of the reliability and applicability of this estimator in scenarios where measurement error is a relevant consideration.