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Eguchi, Shinto - Institute of Statistical Mathematics (Japan)
Robustifying AdaBoost by adding the naive error rate
Robust Principal Component Analysis with Adaptive Selection for Tuning Parameters
A Class of Robust Principal Component Vectors (A Revised Manuscript)
Local Model Uncertainty and Incomplete Data Bias
Image classification based on Markov random field models with Jeffreys divergence
ON LOCAL LIKELIHOOD DENSITY ESTIMATION WHEN THE BANDWIDTH IS LARGE
A paradox concerning nuisance parameters and projected estimating functions
Information Geometry of U-Boost and Bregman Divergence
Genotyping of single nucleotide polymorphism using model-based clustering
Local Sensitivity Approximations for Selectivity Bias University of Warwick, UK
Recent Developments in Discriminant Analysis from an Information Geometric Point of View
The In uence Function of Principal Component Analysis by Self-Organizing Rule
Pharmacokinetic Parameter Estimations by Minimum Relative Entropy Method
A class of logistic-type discriminant functions By SHINTO EGUCHI
A Class of Local Likelihood Methods and Near-Parametric Asymptotics
Modeling late entry bias in survival analysis Masaaki Matsuura
Information Geometry and Statistical Pattern Recognition Shinto Eguchi
(a) Original Data Depth steps
A Comparison of Methods for Estimating Individual Pharmacokinetic Parameters
