Thomas S. Ferguson is a prominent figure in the field of statistics and decision theory, particularly known for his work in Bayesian statistics. He has made significant contributions to mathematical statistics, including the development of the Ferguson-Dirichlet process, which is a foundational concept in nonparametric Bayesian statistics. Ferguson's research includes topics such as estimation, Bayesian inference, and stochastic processes. His work has been influential in various applications, including genetics, economics, and machine learning.
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