Importance Sampling for Context-Dependent Evolutionary Models

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2025

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Abstract

This thesis focuses on optimizing and applying the importance sampling algorithm for context-dependent evolutionary models. First, we use variational inference to update the parameters of the independent-site model as proposal distribution to optimize the importance sampling algorithm. Then, we try blockwise importance sampling algorithm to optimize the importance sampling algorithm. Finally we apply the importance sampling algorithm to estimate unknown parameters given the start and end sequences over a specified time interval.

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Master's thesis

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Statistical Science

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Statistics

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https://hdl.handle.net/10161/33415

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https://creativecommons.org/licenses/by-nc-nd/4.0/

Citation

Xu, Kewei (2025). Importance Sampling for Context-Dependent Evolutionary Models. Master's thesis, Duke University. Retrieved from https://hdl.handle.net/10161/33415.

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