We propose a ratio estimator to determine population estimates using capture-recapture sampling. It's different than traditional approaches in the following ways: (1) Ordering of recaptures: Currently data sets do not take into account the "ordering" of the recaptures, although this crucial information is available to them at no cost. (2) Dependence of trials and cluster sampling: Our model explicitly considers trials to be dependent and improves existing literature which assumes independence. (3) Rate of convergence: The percentage sampled has an inverse relationship with population size, for a chosen degree of accuracy. (4) Asymptotic Attainment of Minimum Variance (Open Systems: (=population variance). (5) Full use of data and model applicability (6) Non-parametric (7) Heterogeneity: When units being sampled are hard to identify. (8) Open and closed systems: Simpler results are presented separately for closed systems. (9) Robustness to assumptions in open systems
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd-5569 |
| Date | 01 January 2014 |
| Creators | Rehman, Zia |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations |
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