矢田 和善(ヤタ カズヨシ)
- 論文
- 高次元小標本におけるサポートベクターマシンの一致性について (Statistical Inference on Divergence Measures and Its Related Topics)
中山 優吾; 矢田 和善; 青嶋 誠
数理解析研究所講究録/1999/pp.17-27, 2016-07 - Estimation of a signal matrix for high-dimensional non-Gaussian data (Statistical Inference on Divergence Measures and Its Related Topics)
矢田 和善; 青嶋 誠
数理解析研究所講究録/1999/pp.36-46, 2016-07 - Reconstruction of a High-Dimensional Low-Rank Matrix
Yata Kazuyoshi; Aoshima Makoto
Electronic Journal of Statistics/10/pp.895-917, 2016-03 - Reconstruction of a signal matrix for high-dimension, low-sample-size data (New Advances in Statistical Inference and Its Related Topics)
村山 航; 矢田 和善; 青嶋 誠
数理解析研究所講究録/1954/pp.23-31, 2015-06 - 拡張クロスデータ行列法と共分散行列関数の不偏推定
矢田 和善; 青嶋 誠
数理解析研究所講究録/1954/pp.51-60, 2015-06 - 高次元小標本における混合データの幾何学的表現とクラスター分析への応用 (Asymptotic Statistics and Its Related Topics)
矢田 和善; 青嶋 誠
数理解析研究所講究録/1910/pp.125-133, 2014-08 - 高次元データの統計的方法論(日本統計学会研究業績賞受賞者特別寄稿論文)
青嶋 誠; 矢田 和善
日本統計学会誌. シリーズJ/43(1)/pp.123-150, 2013-09 - Correlation tests for high-dimensional data using extended cross-data-matrix methodology
Yata Kazuyoshi; Aoshima Makoto
JOURNAL OF MULTIVARIATE ANALYSIS/117/pp.313-331, 2013-05 - A distance-based, misclassification rate adjusted classifier for multiclass, high-dimensional data
Aoshima Makoto; Yata Kazuyoshi
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS/66(5)/pp.983-1010, 2014-10 - Asymptotic normality for inference on multisample, high-dimensional mean vectors under mild conditions
Aoshima Makoto; Yata Kazuyoshi
Methodology and Computing in Applied Probability/17(2)/pp.419-439, 2015-06 - PCA consistency for the power spiked model in high-dimensional settings
Yata Kazuyoshi; Aoshima Makoto
JOURNAL OF MULTIVARIATE ANALYSIS/122/pp.334-354, 2013-11 - 論説： 高次元小標本における統計的推測
青嶋 誠; 矢田和善
數學/65(3)/pp.225-247, 2013-07 - Two-stage equivalence tests that control both size and power
K. Yata
Seq. Anal./27/p.185-200, 2008-01 - Two-stage selection of the best signal-to-noise ratio with related approximations
M. Aoshima; N. Mukhopadhyay; K. Yata
Calcutta Statist. Assoc. Bull./61/p.61-86, 2009-01 - PCA consistency for non-Gaussian data in high dimension, low sample size context
K. Yata; M. Aoshima
Commun. Statist.-Theory Meth./38/p.2634-2652, 2009-01 - Effective two-stage estimation for a linear function of high-dimensional Gaussian means
K. Yata
Seq. Anal./29/p.463-482, 2010-01 - Effective methodologies for statistical inference on microarray studies
M. Aoshima; K.Yata; +矢田 和善
Prostate Cancer-From Bench to Bedside/pp.13-32, 2011-01 - Authors' response to discussions of ``Two-stage procedures for high-dimensional data"
M. Aoshima; K.Yata; +矢田 和善
Seq. Anal./30/p.432-440, 2011-01 - Two-stage procedures for high-dimensional data (Editor's special invited paper)
M. Aoshima; K. Yata
Seq. Anal./30/p.356-399, 2011-01 - Note on classification for high-dimensional data (A New Perspective to Statistical Models and Its Related Topics)
永橋 幸大; 矢田 和善; 青嶋 誠
数理解析研究所講究録/1804(0)/pp.40-52, 2012-08 - Asymptotic properties of a distance-based classifier for high-dimensional data (A New Perspective to Statistical Models and Its Related Topics)
矢田 和善; 青嶋 誠
数理解析研究所講究録/1804(0)/pp.53-64, 2012-08 - Inference on High-Dimensional Mean Vectors with Fewer Observations Than the Dimension
Yata Kazuyoshi; Aoshima Makoto
METHODOLOGY AND COMPUTING IN APPLIED PROBABILITY/14(3)/pp.459-476, 2012-09 - Effective PCA for high-dimension, low-sample-size data with noise reduction via geometric representations
Yata Kazuyoshi; Aoshima Makoto
JOURNAL OF MULTIVARIATE ANALYSIS/105(1)/pp.193-215, 2012-02 - 高次元小標本における平均ベクトルの推測とその周辺 (推測における統計的情報とそれに関連する話題)
矢田 和善
数理解析研究所講究録/1758(0)/pp.136-149, 2011-08 - Note on robust model selection by density power divergence in a contaminated regression model (Statistical Information in Inference and Its Related Topics)
矢田 和善; 青嶋 誠; 小林 裕子
数理解析研究所講究録/1758(0)/pp.150-159, 2011-08 - さらに表示...
- 高次元小標本におけるサポートベクターマシンの一致性について (Statistical Inference on Divergence Measures and Its Related Topics)