Detection Methods for Astronomical Time Series by

In this dissertation I explore and develop statistical methodology motivated by the scientific goals and engineering constraints of the Taiwan-America-Occultation-Survey (TAOS), a large astronomy survey dedicated to understanding populations in our outer solar system. I derive minimal conditions under which detection procedures are valid and robust, discuss the filtering and diagnostics necessary to meet those conditions, and explain how detection results lead to inference about population parameters. I also develop and compare several parametric and non-parametric detection methods for use with TAOS data, and also for the proposed TAOS II survey, which will have higher-resolution data and lower noise levels