Goodness-of-Fit Diagnostics for Capture-Recapture Models

This project aims to develop novel goodness-of-fit diagnostic tools for capture-recapture models, which are widely employed to estimate unknown population sizes in various fields, including wildlife biology and sociology. While several numerical goodness-of-fit tests exist for assessing the reliability of these models, the development of visual diagnostic tools remains under-explored. Building upon existing framework established by Stoklosa et al. and incorporating ideas from Warton et al., this project will implement Dunn-Smyth residuals and evaluate their effectiveness through both real and simulated data.

Bernice Laitly

The University of New South Wales

Bernice Laitly is a highly motivated third-year Statistics student at the University of New South Wales, with an interest in the real-world applications of statistical methods and their role in supporting informed decision-making. She is excited to be involved in mathematical research through the AMSI Summer Research program, where she will explore diagnostic tools in statistics and further develop her approach to statistical analysis. In the future, Bernice envisions a career that combines her passion for technology with her analytical skills to make a meaningful impact.

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