Kyushu University Institute of Mathematics for Industry

KURATA, Sumito

Assistant Professor

Researcher Information Research and Technical Catalog

In real data, there frequently exist some outliers (observations that are markedly different in value from others) derived from, for example, unusual abilities, catastrophe-level phenomena, or human errors. It is difficult to provide a clear definition or threshold of such outliers, moreover, it is effectively impossible to prevent their occurrence. Thus, robust methods that reduce the influence of outliers have a large significance.
My research focuses on robust analytical methods, especially in the model selection problems. I aim to find out a model that can adequately represent phenomena and behavior in a wide range of fields, by utilizing statistical divergence, a measure of farness between probability distributions, to examine the closeness of the underlying “true distribution” and models.

Keywords Statistical Science, Model Selection, Robustness
Division Division of Industrial and Mathematical Statistics
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