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Probability and Statistics (Yuzo Maruyama) Lab
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The lab uses theory to judge how good different methods of inference from data really are.

AboutAbout the lab
Verifying through theory what makes a good estimator.
Prof. Yuzo Maruyama studies mathematical statistics, especially the theory of estimation.
When estimating quantities such as the mean or variance from data, the lab examines theoretically which method is better.
Its main subjects are the admissibility and minimaxity of shrinkage estimators such as the James-Stein estimator.
The lab also investigates the properties of estimators constructed with Bayesian statistics, which uses prior distributions.
Key terms
- Shrinkage estimator
- An estimation method that reduces the average error by pulling estimates slightly toward a common center
- Minimaxity
- The property of keeping the error in the worst-case scenario as small as possible
- Bayesian statistics
- An approach to inference that combines prior beliefs held before seeing the data (the prior distribution) with the observed data
NewsLab news
A paper by Prof. Maruyama and colleagues was published in Stat
A paper by Prof. Maruyama and colleagues was published in Journal of Multivariate Analysis
A paper by Prof. Maruyama and colleagues was published in Japanese Journal of Statistics and Data Science
ResearchResearch themes
Specializes in mathematical statistics and data science.
View More ↗MembersFaculty
- ProfessorYuzo Maruyama
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The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “Galton box 2” Klaus-Dieter Keller / Public domain (cropped)
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- Related lab (Probability and Statistics (Takashi Imamura)): “Brownian trajectory” Roque345 / CC BY 3.0 (cropped)
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