AOSHIMA Makoto
- Articles
- 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 - 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 - Two-stage procedures for high-dimensional data (Editor's Special Invited Paper)
Aoshima; M.; Yata; K.; +青嶋 誠
Sequential Analysis/30/pp.356-399, 2011-01 - Authors' response: Two-stage procedures for high-dimensional data
Aoshima; M.; Yata; K.; +青嶋 誠
Sequential Analysis/30/pp.432-440, 2011-01 - 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 - Asymptotic second-order consistency for two-stage estimation methodologies and its applications
Aoshima Makoto; Yata Kazuyoshi
ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS/62(3)/pp.571-600, 2010-06 - Effective PCA for high-dimension, low-sample-size data with singular value decomposition of cross data matrix
Yata Kazuyoshi; Aoshima Makoto
JOURNAL OF MULTIVARIATE ANALYSIS/101(9)/pp.2060-2077, 2010-10 - Intrinsic Dimensionality Estimation of High-Dimension, Low Sample Size Data with D-Asymptotics
Yata Kazuyoshi; Aoshima Makoto
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS/39(8-9)/pp.1511-1521, 2010-01 - PCA Consistency for Non-Gaussian Data in High Dimension, Low Sample Size Context
Yata Kazuyoshi; Aoshima Makoto
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS/38(16-17)/pp.2634-2652, 2009-01 - Double shrink methodologies to determine the sample size via covariance structures
Yata Kazuyoshi; Aoshima Makoto
JOURNAL OF STATISTICAL PLANNING AND INFERENCE/139(2)/pp.81-99, 2009-02 - Optimal discriminant functions for normal populations
Wakaki Hirofumi; Aoshima Makoto
JOURNAL OF MULTIVARIATE ANALYSIS/100(1)/pp.58-69, 2009-01 - Cluster analysis for high-dimensional data
Aoshima Makoto
Proceedings of Statistical Inference for High-Dimensional Data and Its Applications/pp.11-20, 2012 - 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
RIMS Kokyuroku/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
RIMS Kokyuroku/1804(0)/pp.53-64, 2012-08 - 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 - Two-stage procedures for estimating the difference of means when the sampling cost is different
Aoshima; M.; Mukhopadhyay; N.; Kobayashi; Y.; +青嶋 誠
Sequential Analysis/30/pp.160-171, 2011-01 - Note on robust estimation and model selection in a contaminated mixture model (Statistical Experiment and Its Related Topics)
小林 裕子; 矢田 和善; 青嶋 誠
RIMS Kokyuroku/1703(0)/pp.159-179, 2010-08 - A path to the special issue on Recent Advances in Statistical Inference -in Honor of Professor Masafumi Akahira
Aoshima M.
Commun. Statist. Theory and Methods/39/p.1321-1323, 2010-01 - A Path to the Special Issue on Recent Advances in Statistical InferenceIn Honor of Professor Masafumi Akahira
Aoshima Makoto
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS/39(8-9)/pp.1321-1323, 2010-01 - The Professional Career and Contributions of Professor Masafumi Akahira
Aoshima Makoto; Koike Ken-Ichi
COMMUNICATIONS IN STATISTICS-THEORY AND METHODS/39(8-9)/pp.1324-1342, 2010-01 - Asymptotically optimal allocation for multiple comparisons with a control when variances are unknown and unequal
Aoshima; M.; Takada; Y.; +青嶋 誠
Amer. J. Math. Manage. Sci./29/p.125-137, 2009-01 - Eigenvalue estimation for high dimension, Gaussian data and sample size determination
Aoshima; M.; Yata; K.; +青嶋 誠
IWSM 2009 proceedings, 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 - 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 - 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(0)/pp.112-129, 2009-01 - more...
- Effective PCA for high-dimension, low-sample-size data with noise reduction via geometric representations