ホーム > 青嶋 誠/ Aoshima, Makoto
青嶋 誠
Aoshima, Makoto
数理物質系 数学域 , 教授 Institute of Mathematics , Professor
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1.
Automatic Sparse PCA for High-Dimensional Data
Kazuyoshi Yata; Makoto Aoshima
Statistica Sinica (2025) Semantic Scholar
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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
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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
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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
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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
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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)
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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
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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
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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
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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)
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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
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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)
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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)
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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)
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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)
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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)
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17.
High-dimensional quadratic classifiers in non-sparse settings
AOSHIMA Makoto; YATA Kazuyoshi
Methodology and Computing in Applied Probability 21: 663 (2019)
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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)
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19.
Two-sample tests for high-dimension, strongly spiked eigenvalue models
AOSHIMA Makoto; YATA Kazuyoshi
Statistica Sinica 28: 43 (2018) Semantic Scholar
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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
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2.
Effective Methodologies for Statistical Inference on Microarray Studies
AOSHIMA Makoto; YATA Kazuyoshi
(担当:分担執筆)
InTech 2011年
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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
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4.
Recent Advances in Statistical Inference- in Honor of Professor Masafumi Akahira
AOSHIMA Makoto
Taylor & Francis 2010年
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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
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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
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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
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8.
Multivariate Statistical Analysis in Honor of Professor Minoru Siotani, Vol. 3
HAYAKAWA Takesi; AOSHIMA Makoto; SHIMIZU Kunio
American Sciences Press 1997年
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9.
Multivariate Statistical Analysis in Honor of Professor Minoru Siotani, Vol. 2
HAYAKAWA Takesi; AOSHIMA Makoto; SHIMIZU Kunio
American Sciences Press 1996年
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10.
多変量解析
数理情報科学事典 朝倉書店 1995年
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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
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12.
Multivariate Statistical Analysis in Honor of Professor Minoru Siotani, Vol. 1
HAYAKAWA Takesi; AOSHIMA Makoto; SHIMIZU Kunio
American Sciences Press 1995年
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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
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1.
Non-Sparse Modeling for High-Dimensional Data (特別招待講演)
AOSHIMA Makoto
Statistische Woche 2023, Dortmund, Germany 2023年9月 招待有り
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2.
高次元現象の統計数理(企画特別講演)
青嶋 誠
日本数学会2022年度秋季総合分科会 2022年9月 招待有り
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3.
高次元小標本の統計学:非スパース性と巨大ノイズ(特別講演)
青嶋 誠
統計数理研究所リスク解析戦略研究センターシンポジウム 2021年9月 招待有り
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4.
High-Dimensional Statistical Analysis: Non-Sparsity, Strongly Spiked Noise and HDLSS (基調講演)
AOSHIMA Makoto
The 7th International Workshop in Sequential Methodologies, State University of New York, U.S.A. 2019年6月 招待有り
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5.
Non-Sparse Modeling for High-Dimensional Data (招待講演)
AOSHIMA Makoto
Waseda International Symposium “Introduction of General Causality to Various Data & its Applications”, Waseda University 2019年2月 招待有り
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6.
New Techniques in High-Dimensional Statistical Analysis: SSE vs. NSSE and Data Transformation (基調講演)
AOSHIMA Makoto
2018 Workshop on High-Dimensional Statistical Analysis, Academia Sinica, Taiwan 2018年12月 招待有り
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7.
High-Dimensional Statistical Analysis: Non-Sparse Modeling, Geometric Representations and New PCAs (基調講演)
AOSHIMA Makoto
2018 Workshop on High-Dimensional Statistical Analysis, Academia Sinica, Taiwan 2018年12月 招待有り
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8.
New techniques in high-dimensional statistical analysis (招待講演)
AOSHIMA Makoto
Waseda International Symposium “Introduction of General Causality to Various Data & Its Innovation of The Optimal Inference”, Waseda University 2018年10月 招待有り
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9.
計量生物学における高次元統計解析の可能性(招待講演)
青嶋 誠
2018年度統計関連学会連合大会,中央大学 2018年9月 招待有り
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10.
High-dimensional statistical analysis: Spiked models and data transformation(特別招待講演)
AOSHIMA Makoto
The 2nd International Conference on Econometrics and Statistics, City University of Hong Kong, Hong Kong 2018年6月 招待有り
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11.
High-dimensional statistical analysis under spiked models(招待講演)
AOSHIMA Makoto
The Fourth Conference of the International Society for Nonparametric Statistics, Salerno, Italy 2018年6月 招待有り
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12.
High-Dimensional Statistical Analysis by Non-Sparse Modeling(招待講演)
AOSHIMA Makoto
Waseda International Symposium “Recent Developments in Time Series Analysis: Quantile Regression, High Dimensional Data & Causality", Waseda University 2018年2月 招待有り
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13.
高次元統計解析:理論・方法論とその周辺(日本統計学会賞受賞者記念講演)
青嶋 誠
2017年度統計関連学会連合大会,南山大学 2017年9月 招待有り
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14.
PCA based clustering for ultrahigh-dimensional data(招待講演)
AOSHIMA Makoto
The 1st International Conference on Econometrics and Statistics, Hong Kong University of Science and Technology, Hong Kong 2017年6月 招待有り
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15.
High-dimensional Statistical Analysis for the SSE Model(招待講演)
AOSHIMA Makoto
A Symposium on Complex Data Analysis 2017, National Tsing Hua University, Hsinchu, Taiwan 2017年5月 招待有り
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16.
高次元固有空間の推測と高次元統計解析(招待講演)
青嶋 誠
第11回日本統計学会春季集会,政策研究大学院大学 2017年3月 招待有り
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17.
High-dimensional statistical analysis based on the inference of eigenstructures(招待講演)
AOSHIMA Makoto
Waseda International Symposium “High Dimensional Statistical Analysisfor Time Spatial Processes & Quantile Analysis for Time Series”, Waseda University 2017年2月 招待有り
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18.
高次元の統計学 (再び)(招待講演)
青嶋 誠
統計数理および金融数理研究セミナー, 早稲田大学 2016年4月 招待有り
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19.
High-Dimensional Classification in Non-Sparse Settings(招待講演)
AOSHIMA Makoto
Kumamoto International Symposium ``High Dimensional Statistical Analysis and Quantile Analysis for Time Series", Kumamoto University 2016年3月 招待有り
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20.
高次元の統計学 (招待講演)
青嶋 誠
日本数学会2016年度年会市民講演会, 筑波大学 2016年3月 招待有り
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