ホーム > 矢田和善/ Yata, Kazuyoshi

矢田和善

Yata, Kazuyoshi

数理物質系 , 教授
Institute of Pure and Applied Sciences , Professor

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。

41. 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: 150 (2011)
42. Effective methodologies for statistical inference on microarray studies M., Aoshima; K.Yata; 矢田, 和善
Prostate Cancer-From Bench to Bedside 13 (2011)
43. Authors' response to discussions of ``Two-stage procedures for high-dimensional data" M., Aoshima; K.Yata; 矢田, 和善
Seq. Anal. 30: 432-440 (2011)
44. Two-stage procedures for high-dimensional data (Editor's special invited paper) M., Aoshima; K., Yata
Seq. Anal. 30: 356-399 (2011)
45. Effective PCA for high-dimension, low-sample-size data with singular value decomposition of cross data matrix Kazuyoshi Yata; Makoto Aoshima
JOURNAL OF MULTIVARIATE ANALYSIS 101: 2060 (2010) Semantic Scholar
46. Effective methodologies for high-dimension, low sample size data (Statistical experiment and its related topics--RIMS共同研究報告集) 矢田, 和善
RIMS Kokyuroku 1703: 180 (2010)
47. Note on robust estimation and model selection in a contaminated mixture model (Statistical experiment and its related topics--RIMS共同研究報告集) 小林, 裕子; 矢田, 和善; 青嶋, 誠
RIMS Kokyuroku 1703: 159 (2010)
48. Asymptotic second-order consistency for two-stage estimation methodologies and its applications Makoto Aoshima; Kazuyoshi Yata
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS 62: 571 (2010) Semantic Scholar
49. Effective two-stage estimation for a linear function of high-dimensional Gaussian means K., Yata
Seq. Anal. 29: 463-482 (2010)
50. Intrinsic dimensionality estimation of high-dimension, low sample size data with D-Asymptotics Kazuyoshi Yata; Makoto Aoshima
Communications in Statistics - Theory and Methods 39: 1511 (2010) Semantic Scholar
51. Double shrink methodologies to determine the sample size via covariance structures Kanyoshi Yata; Makoto Aoshima
JOURNAL OF STATISTICAL PLANNING AND INFERENCE 139: 81 (2009) Semantic Scholar
52. PCA consistency for non-Gaussian data in high dimension, low sample size context K., Yata; M., Aoshima
Commun. Statist.-Theory Meth. 38: 2634-2652 (2009)
53. Two-stage selection of the best signal-to-noise ratio with related approximations M., Aoshima; N; Mukhopadhyay; K., Yata
Calcutta Statist. Assoc. Bull. 61: 61-86 (2009)
54. PCA Consistency for Non-Gaussian Data in High Dimension, Low Sample Size Context Kazuyoshi Yata; Makoto Aoshima
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 38: 2634 (2009) Semantic Scholar
55. 高次元小標本における固有値の推定とその応用 (統計的推測へのベイズ的アプローチとそれに関連する話題) 矢田, 和善; 青嶋, 誠
RIMS Kokyuroku 1621: 112 (2009)
56. Note on estimating the intrinsic dimension of high dimension, low sample size data (種々のモデルの統計的解析--RIMS共同研究報告集) 矢田, 和善; 青嶋, 誠
RIMS Kokyuroku 1603: 130 (2008)
57. Two-stage equivalence tests that control both size and power K., Yata
Seq. Anal. 27: 185-200 (2008)
58. Asymptotic Second-Order Consistency For Fixed-Size Estimation and Its Applications(Statistical Decision for Multiple Comparison and Its Related Topics) 矢田, 和善; 青嶋, 誠
RIMS Kokyuroku 1560: 80 (2007)

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1. 高次元の統計学青嶋, 誠; 矢田, 和善
共立出版 2019年4月 (ISBN: 9784320112636)

1. Asymptotic properties of high-dimensional kernel PCA and its applications Nakayama, Yugo; Yata, Kazuyoshi; Aoshima, Makoto
International Symposium on New Developments of Theories and Methodologies for Large Complex Data 2021年11月6日招待有り
2. Sparse PCA for high-dimensional data based on the noise-reduction methodology and its application Yata, Kazuyoshi; Aoshima, Makoto
The 63rd ISI World Statistics Congress 2021年7月14日招待有り
3. Clustering by kernel PCA with Gaussian kernel and tuning for high-dimensional data Nakayama, Yugo; Yata, Kazuyoshi; Aoshima, Makoto
The 4th International Conference on Econometrics and Statistics 2021年6月26日招待有り
4. Tests for covariance structures in high-dimensional data Yata, Kazuyoshi; Ishii, Aki; Aoshima, Makoto
The 4th International Conference on Econometrics and Statistics 2021年6月26日招待有り
5. High-dimensional classifiers under the strongly spiked eigenvalue model Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
The 4th International Conference on Econometrics and Statistics 2021年6月25日招待有り
6. High-dimensional quadratic classifiers under the strongly spiked eigenvalue model Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
IISA 2021 Conference 2021年5月21日招待有り
7. 高次元におけるカーネル主成分分析の漸近的性質と異常値の検出への応用中山優吾; 矢田和善; 青嶋誠
日本数学会年度年会 2021年3月16日
8. 距離加重判別分析の高次元漸近的性質江頭健斗; 矢田和善; 青嶋誠
日本数学会年度年会 2021年3月16日
9. 高次元固有ベクトルの検定について石井晶; 矢田, 和善; 青嶋誠
日本数学会秋季総合分科会 2020年9月24日
10. Clustering by kernel principal component analysis for high-dimensional data 中山優吾; 矢田和善; 青嶋誠
日本数学会秋季総合分科会 2020年9月24日
11. 高次元データにおける距離加重判別分析の漸近的性質とバイアス補正江頭健斗; 矢田和善; 青嶋誠
統計関連学会連合大会 2020年9月11日
12. 高次元小標本における異常値の検出中山優吾; 矢田和善; 青嶋誠
統計関連学会連合大会 2020年9月10日
13. Tests of high-dimensional correlation matrices under the strongly spiked eigenvalue model 石井晶; 矢田和善; 青嶋誠
統計関連学会連合大会 2020年9月10日
14. 高次元スパースPCAの一致性とその応用矢田和善; 青嶋誠
統計関連学会連合大会 2020年9月10日
15. Tests for high-dimensiomal covariance structures under the SSE model Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
International Symposium on Theories and Methodologies for Large Complex Data 2019年11月21日招待有り
16. Inference on mean vectors for high-dimensional data with the strongly spiked eigenstructure Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
The 3rd International Conference on Econometrics and Statistics 2019年6月26日招待有り
17. A high-dimensional quadratic classifier by data transformation for strongly spiked eigenvalue models Yata, Kazuyoshi; Ishii, Aki; Aoshima, Makoto
The 3rd International Conference on Econometrics and Statistics 2019年6月26日招待有り
18. A high-dimensional quadratic classifier under the strongly spiked eigenvalue model Yata, Kazuyoshi; Ishii, Aki; Aoshima, Makoto
The 14th Workshop on Stochastic Models, Statistics and their Application 2019年3月6日招待有り
19. Tests of High-Dimensional Mean Vectors and Its Application Under the SSE Model Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
Waseda International Symposium “Introduction of General Causality to Various Data & its Applications” 2019年2月26日招待有り
20. Tests of high-dimensional mean vectors under the SSE model Ishii, Aki; Yata, Kazuyoshi; Aoshima, Makoto
International Symposium on Statistical Theory and Methodology for Large Complex Data 2018年11月26日招待有り