大谷内奈穂 | 筑波大学数理物質科学研究科

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概要

関連著者

著作論文

Maximal orders of convergence of consistency in terms of measures of diversity(Statistical Decision for Multiple Comparison and Its Related Topics)
On the Kiefer type information inequality applicable to a family of truncated distributions(Statistical Conditional Inference and Its Related Topics)
Lower bounds for the Bayes risk of unbiased estimators in non-regular cases (Statistical Inference of Records and Related Statistics)
An information inequality for the Bayes risk applicable to non-regular cases (Approximations to the Statistical Distributions)
Asymptotic efficiencies of estimators in a one-parameter family of truncated distributions (Approximations to the Statistical Distributions)
Asymptotics of the Maximum Probability Estimators in Statistical Experiments (Statistical Experiments and Clinical Trials)
On lower bounds for the Bayes risk of estimators in the uniform and truncated normal cases (Statistical Inference and the Bioequivalence Problem)
The Amount of Partial Information and Sufficiency (Statistical Region Estimation and Its Application)
Bayes estimation under the LINEX loss (種々のモデルの統計的解析--RIMS共同研究報告集)
Amounts of information and inequalities for the Bayes risk (統計的条件付推測とそれに関連する話題 RIMS共同研究報告集)
Remarks on uniformly minimum variance unbiased estimation (Statistical Information in Inference and Its Related Topics)
The non-regular statistical structure from the viewpoint of the loss of information (Statistical Information in Inference and Its Related Topics)
Remarks on uniformly minimum variance unbiased estimation (推測における統計的情報とそれに関連する話題--RIMS共同研究報告集)
The non-regular statistical structure from the viewpoint of the loss of information (推測における統計的情報とそれに関連する話題--RIMS共同研究報告集)
The asymptotic expansion of the maximum likelihood estimator for a truncated exponential family of distributions (A New Perspective to Statistical Models and Its Related Topics)
統計的非正則推定における Bayes 的アプローチによる情報不等式
Asymptotic comparison of estimators for a family of truncated distributions (Asymptotic Expansions for Various Models and Their Related Topics)

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