Senior Project Advisor
Kimihiro Noguchi, Ramadha Piyada Gamage
bootstrap, change point analysis, likelihood ratio test, nonparametric test
Change point analysis is the process of determining changes to the mean of a sequence of independent observations. The goal is to determine the location of the change and how the change impacts the parameter in question. In this project, we applied the likelihood ratio test (LR) which uses a binary segmentation method to split the data at each change point. The data is iteratively split at each change point until every location of change is identified. The p-value is typically computed using the asymptotic distribution of the test statistic, however, it can be unreliable when the number of observations is too small. To improve our analysis of change points, we carried out a simulation study to analyze the empirical Type I error rate and the power of the LR test, using the parametric and nonparametric bootstrap. Under normal and exponential distributions it is found that the nonparametric bootstrap method makes the test reliable and robust for small, moderate, and large sample sizes. The improved bootstrap method is then applied to a real data set.
Donovan, Lili, "Bootstrapping the Likelihood Ratio Test To Determine Change Points" (2022). WWU Honors College Senior Projects. 599.
Subjects - Topical (LCSH)
Bootstrap (Statistics)--Computer simulation
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