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Ohyauchi Lab
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A mathematics lab that studies statistical estimation in non-regular cases.

AboutAbout the lab
Statistical estimation in non-regular cases.
The Ohyauchi Lab's research topic is statistical non-regular estimation theory.
The faculty list of the Mathematics Degree Program describes the research as “a study of statistical non-regular estimation theory from a Bayesian approach.”
Its research fields are registered as Applied Mathematics and Statistics, and Foundations of Mathematics.
The professor's researcher information page (researchmap) lists papers and talks.
Key terms
- Non-regular
- Cases in which the conditions assumed by ordinary estimation theory do not hold
- Maximum likelihood estimator
- An estimator that takes as the estimate of an unknown value the one that maximizes the probability of obtaining the observed data
- Truncated distribution family
- A family of probability distributions whose range of possible values is cut off on one or both sides
ResearchResearch themes
The lab's research topic is statistical non-regular estimation theory. The professor's papers deal with topics such as the asymptotic loss incurred when the truncation parameter of a truncated distribution family is estimated by the maximum likelihood estimator.
View More ↗MembersFaculty
- Assistant ProfessorNao Ohyauchi
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Report an errorAbout the images
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: “Jeffreys prior probability for the beta distribution - J. Rodal” Dr. J. Rodal / CC BY-SA 3.0 (cropped)
- A Bayesian Study of Statistical Non-Regular Estimation Theory: “TheBiLLeLottoBallMachine2012” Graphoscanada / CC BY-SA 3.0 (cropped)
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