seminars:stat:feb152024 [Department of Mathematics and Statistics, Binghamton University]

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<WRAP centeralign>##Statistics Seminar##\\ Department of Mathematics and Statistics</WRAP>

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^  **DATE:**|Thursday, February 15, 2024 |
^  **TIME:**|1:15pm -- 2:15pm |
^  **LOCATION:**|WH 100E |
^  **SPEAKER:**|Wenshu Dai, Binghamton University |
^  **TITLE:**|The mixture of logistic t multinomial models (continued)  |
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<WRAP centeralign>**Abstract**</WRAP>
In the context of analyzing complex, high-dimensional microbiome data, the use of Gaussian mixture models is becoming more common. Although applying a multinomial distribution takes into account the compositional nature of the data and a Gaussian prior provides versatility in modeling covariance matrices, it is important to note the potential for heavy-tailed distributions in log-ratio transformed microbiome data. To address this, our research introduces a more resilient model: a mixture of logistic t-multinomial models. This model is designed to work with the hierarchical structures of the log-ratio transformed compositional data, providing a more robust alternative to the normal distribution with longer tails. Additionally, we incorporate a variational Gaussian approximation alongside the Expectation-Maximization (EM) algorithm, which aids in the effective estimation of parameters.
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