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青嶋誠

Aoshima, Makoto

数理物質系数学域 , 教授
Institute of Mathematics , Professor

https://www.math.tsukuba.ac.jp/~aoshima-lab/jp/

オープンアクセス版の論文は「つくばリポジトリ」で読むことができます。

1. Automatic Sparse PCA for High-Dimensional Data Kazuyoshi Yata; Makoto Aoshima
Statistica Sinica (2025) Semantic Scholar
2. Test for high-dimensional outliers with principal component analysis Yugo Nakayama; Kazuyoshi Yata; Makoto Aoshima
Japanese Journal of Statistics and Data Science (2024) Semantic Scholar
3. High-dimensional Statistical Analysis and Its Application to an ALMA Map of NGC 253 Tsutomu T. Takeuchi; Kazuyoshi Yata; Kento Egashira; Makoto Aoshima (+4 著者) Kai T. Kono
The Astrophysical Journal Supplement Series 271: 44 (2024) Semantic Scholar
4. Asymptotic properties of hierarchical clustering in high-dimensional settings Kento Egashira; Kazuyoshi Yata; Makoto Aoshima
Journal of Multivariate Analysis 199: 105251 (2024) Semantic Scholar
5. Geometric classifiers for high-dimensional noisy data ISHII Aki; YATA Kazuyoshi; AOSHIMA Makoto
Special Issue: 50th Anniversary Jubilee Edition, Journal of Multivariate Analysis 188: 104850 (2022) Semantic Scholar
6. 論説：高次元小標本における統計的仮説検定青嶋誠; 石井晶; 矢田和善
数学 73: 360 (2021)
7. Asymptotic properties of distance-weighted discrimination and its bias correction for high-dimension, low-sample-size data EGASHIRA Kento; YATA Kazuyoshi; AOSHIMA Makoto
Japanese Journal of Statistics and Data Science 4: 821 (2021) Semantic Scholar
8. Clustering by principal component analysis with Gaussian kernel in high-dimension, low-sample-size settings NAKAYAMA Yugo; YATA Kazuyoshi; AOSHIMA Makoto
Journal of Multivariate Analysis 185: 104779 (2021) Semantic Scholar
9. Hypothesis tests for high-dimensional covariance structures ISHII Aki, YATA Kazuyoshi, AOSHIMA Makoto
Annals of the Institute of Statistical Mathematics 73: 599 (2021) Semantic Scholar
10. 単一強スパイク固有値モデルにおける高次元平均ベクトルの2標本検定石井晶; 矢田和善; 青嶋誠
応用統計学 49: 109 (2020)
11. Geometric consistency of principal component scores for high-dimensional mixture models and its application YATA Kazuyoshi, AOSHIMA Makoto
Scandinavian Journal of Statistics 47: 899 (2020) Semantic Scholar
12. Bias-corrected support vector machine with Gaussian kernel in high-dimension, low-sample-size settings NAKAYAMA Yugo; YATA Kazuyoshi; AOSHIMA Makoto
Annals of the Institute of Statistical Mathematics 72: 1257 (2020)
13. Inference on high-dimensional mean vectors under the strongly spiked eigenvalue model ISHII Aki; YATA Kazuyoshi; AOSHIMA Makoto
Japanese Journal of Statistics and Data Science 2: 105 (2019)
14. Equality tests of high-dimensional covariance matrices under the strongly spiked eigenvalue model ISHII Aki; YATA Kazuyoshi; AOSHIMA Makoto
Journal of Statistical Planning and Inference 202: 99 (2019)
15. Distance-based classifier by data transformation for high-dimension, strongly spiked eigenvalue models AOSHIMA Makoto; YATA Kazuyoshi
Annals of the Institute of Statistical Mathematics 71: 473 (2019)
16. A quadratic classifier for high-dimension, low-sample-size data under the strongly spiked eigenvalue model ISHII Aki, YATA Kazuyoshi, AOSHIMA Makoto
Stochastic Models, Statistics and Their Applications, Proceedings of the 14th Workshop on Stochastic Models, Statistics and their Application 131 (2019)
17. High-dimensional quadratic classifiers in non-sparse settings AOSHIMA Makoto; YATA Kazuyoshi
Methodology and Computing in Applied Probability 21: 663 (2019)
18. 高次元統計解析: 理論と方法論の新しい展開（日本統計学会賞受賞者特別寄稿論文）青嶋誠
Journal of the Japan Statistical Society Japanese issue 48: 89 (2018)
19. Two-sample tests for high-dimension, strongly spiked eigenvalue models AOSHIMA Makoto; YATA Kazuyoshi
Statistica Sinica 28: 43 (2018) Semantic Scholar
20. A test of sphericity for high-dimensional data and its application for detection of divergently spiked noise YATA Kazuyoshi; AOSHIMA Makoto; NAKAYAMA Yugo
Sequential Analysis 37: 397 (2018) Semantic Scholar

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1. 高次元の統計学青嶋誠; 矢田和善 (担当:共著)
共立出版 2019年
2. Effective Methodologies for Statistical Inference on Microarray Studies AOSHIMA Makoto; YATA Kazuyoshi (担当:分担執筆)
InTech 2011年
3. 知識ベース知識の森青嶋誠 (担当:分担執筆, 範囲:12群電子情報通信基礎: 3編統計・確率)
電子情報通信学会 2011年
4. Recent Advances in Statistical Inference- in Honor of Professor Masafumi Akahira AOSHIMA Makoto
Taylor & Francis 2010年
5. Asymptotic Second-Order Efficiency for Two-Stage Multiple Comparisons with Components of a Linear Function of Mean Vectors AOSHIMA Makoto; KUSHIDA Takuya (担当:分担執筆)
Birkhauser 2005年
6. Two-Stage Procedures for Selecting the Best Component of a Multivariate Exponential Distribution AOSHIMA Makoto; AOKI Mitsuru; KAI Masaki (担当:分担執筆)
Dekker 2004年
7. Bounded Risk Point Estimation of a Linear Function of K Multinormal Mean Vectors When Covariance Matrices Are Unknown AOSHIMA Makoto; TAKADA Yoshikazu (担当:分担執筆)
Taylor & Francis 2002年
8. Multivariate Statistical Analysis in Honor of Professor Minoru Siotani, Vol. 3 HAYAKAWA Takesi; AOSHIMA Makoto; SHIMIZU Kunio
American Sciences Press 1997年
9. Multivariate Statistical Analysis in Honor of Professor Minoru Siotani, Vol. 2 HAYAKAWA Takesi; AOSHIMA Makoto; SHIMIZU Kunio
American Sciences Press 1996年
10. 多変量解析
数理情報科学事典朝倉書店 1995年
11. Book review of "Multistage Selection and Ranking Procedures : Second-Order Asymptotics, Mukhopadhyay and Solanky, Marcel Dekker, Inc.(1994)"
J. Japan Statist. Soc. 1995年
12. Multivariate Statistical Analysis in Honor of Professor Minoru Siotani, Vol. 1 HAYAKAWA Takesi; AOSHIMA Makoto; SHIMIZU Kunio
American Sciences Press 1995年
13. Note on Testing the Goodness-of-Fit for Intraclass Correlation Model SIOTANI Minoru; AOSHIMA Makoto (担当:分担執筆)
Elsevier Science Publishers 1988年

21. 非スパース性と高次元データの分類（招待講演）青嶋誠
第18回情報論的学習理論ワークショップ, つくば国際会議場 2015年11月招待有り
22. High-Dimensional Quadratic Classifiers in Non-Sparse Settings under Heteroscedasticity（基調講演） AOSHIMA Makoto
ISNPS Meeting ``Biosciences, Medicine, and novel Non-Parametric Methods", Graz, Austria 2015年7月招待有り
23. Statistical Methods for Heterogeneous Data（パネリスト） AOSHIMA Makoto
ISNPS Meeting ``Biosciences, Medicine, and novel Non-Parametric Methods", Graz, Austria 2015年7月招待有り
24. High-Dimensional Quadratic Classifiers in Non-Sparse Settings （基調講演） AOSHIMA Makoto
Workshop on Statistical Methods for Large Complex Data, National Sun Yat-sen University, Kaohsiung, Taiwan 2015年3月招待有り
25. 高次元データの分類：判別分析とクラスター分析の諸問題と高次元現象（招待講演）青嶋誠
The Applied Statistics Workshop 2014, 東京大学 2014年12月招待有り
26. Quadratic-Type Classifications for Non-Gaussian, High-Dimensional Data（招待講演） AOSHIMA Makoto
Second Conference of the International Society of NonParametric Statistics, Conference Center of Valentin Sancti Petri Hotel, Cadiz, Spain 2014年6月招待有り
27. New PCAs for High-Dimensional Data （招待講演） AOSHIMA Makoto
Workshop on Statistics for High-Dimensional and Dependent Data, National Taiwan University, Taipei, Taiwan 2014年3月招待有り
28. Effective PCA for High-Dimensional Data and Its Applications （招待講演） AOSHIMA Makoto
The 59th World Statistics Congress, Hong Kong Convention and Exhibition Centre, Hong Kong, China 2013年8月招待有り
29. Effective Methodologies for High-Dimensional Data and their Applications （招待講演） AOSHIMA Makoto
STOR Colloquium, Department of Statistics and Operations Research, University of North Carolina, Chapel Hill, North Carolina, U.S.A. 2013年7月招待有り
30. Effective Methodologies for High-Dimensional Data （基調講演） AOSHIMA Makoto
Fourth International Workshop in Sequential Methodologies, University of Georgia, Georgia, U.S.A. 2013年7月招待有り
31. Discussion on Professor Shelemyahu Zacks' Talk （指定討論） AOSHIMA Makoto
Sixth International Workshop on Applied Probability, Jerusalem, Israel 2012年6月招待有り
32. Misclassification Rate Adjusted Classifier for Multiclass, High-Dimensional Data （招待講演） AOSHIMA Makoto
Sixth International Workshop on Applied Probability, Jerusalem, Israel 2012年6月招待有り
33. Effective Methodologies for High-Dimensional Statistical Inference (Invited)
Joint Meeting of the 2011 Taipei International Statistical Symposium and 7th Conference of the Asian Regional Section of the IASC, Academia Sinica, Taipei, Taiwan 2011年12月招待有り
34. Effective Methodologies for High-Dimensional Statistical Inference （招待講演） AOSHIMA Makoto
Joint Meeting of the 2011 Taipei International Statistical Symposium and 7th Conference of the Asian Regional Section of the IASC, Academia Sinica, Taipei, Taiwan 2011年12月招待有り
35. Effective Classification for High-Dimension, Non-Gaussian Data and Sample Size Determination (Invited)
Third International Workshop in Sequential Methodologies,Stanford University, California, U.S.A. 2011年6月招待有り
36. Effective Classification for High-Dimension, Non-Gaussian Data and Sample Size Determination （招待講演） AOSHIMA Makoto
Third International Workshop in Sequential Methodologies, Stanford University, California, U.S.A. 2011年6月招待有り
37. Two-Stage Inference Methods for Large P, Small N Scenarios: Part II (Invited)
The Fifth International Workshop in Applied Probability, Madrid, Spain 2010年7月招待有り
38. Two-Stage Inference Methods for Large P, Small N Scenarios: Part II （招待講演） AOSHIMA Makoto
Fifth International Workshop in Applied Probability, Madrid, Spain 2010年7月招待有り
39. Eigenvalue Estimation for High Dimension, Gaussian Data and Sample Size Determination (Invited)
Second International Workshop in Sequential Methodologies, Troyes, France 2009年6月招待有り
40. Eigenvalue Estimation for High Dimension, Gaussian Data and Sample Size Determination （招待講演） AOSHIMA Makoto
Second International Workshop in Sequential Methodologies,Troyes, France 2009年6月招待有り