Dept. of Statistics

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  • Chen, Yinyin (2020-05-07)
    Despite the fact that latent class models have been widely applied and appeared to perform well in various applications, it is well known that inference for latent class models is challenging due to the potential ...

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  • Yang, Xinming (2020-05-06)
    Group structures arise naturally in a variety of modern data applications and statistical problems in the high-dimensional data setting where the number of variables can greatly exceed the number of observations. The group ...

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  • Yuan, Yubai (2020-04-08)
    Network data has arisen as one of the most common forms of information collection. This is due to the fact that the scope of studies not only focuses on subjects alone, but also on the relationships among subjects. In this ...

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  • Biscarri, William (2019-12-03)
    We propose new methods and frameworks for approaching three different statistical sequence problems. The first is a tree-based computational method for calculating the Poisson Binomial distribution function, which is the ...

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  • Man, Albert (2019-12-04)
    Exploratory factor analysis is a dimension-reduction technique commonly used in psychology, finance, genomics, neuroscience, and economics. Advances in computational power have opened the door for fully Bayesian treatments ...

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