Abundance estimation with a categorical covariate subject to missing in continuous-time capture-recapture studies |
| |
| Authors: | Yang Liu Lin Zhu Guanfu Liu |
| |
| Affiliation: | 1. Key Laboratory of Advanced Theory and Application in Statistics and Data Science - MOE, School of Statistics, East China Normal University, Shanghai, China;2. Institute of Statistics and Big Data, Renmin University of China, Beijing, China;3. School of Statistics and Information, Shanghai University of International Business and Economics, Shanghai, China |
| |
| Abstract: | AbstractIn continuous-time capture-recapture experiments, individual heterogeneity has a large effect on the capture probability. To account for the heterogeneity, we consider an individual covariate, which is categorical and subject to missing. In this article, we develop a general model to summarize three kinds of missing mechanisms, and propose a maximum likelihood estimator of the abundance. A likelihood ratio confidence interval of the abundance is also proposed. We illustrate the proposed methods by simulation studies and a real data example of a bird species prinia subflava in Hong Kong. |
| |
| Keywords: | Abundance continuous-time capture-recapture missing covariate maximum likelihood estimation |
|
|
