Journal papers

[p63]

Density estimation with minimization of U-divergence. K. Naito and S. Eguchi. To appear in Machine Learning, 2012.  [pdf]

[p62]

An extension of the Receiver Operating Characteristic curve and AUC-optimal classification. T. Takenouchi, O. Komori and S. Eguchi. To appear in Neural Computation, 2012.  [pdf]

  [p61]

Boosting learning algorithm for pattern recognition and beyond.  O. Komori and S. Eguchi. IEICE Transactions on Information and Systems, E94-D, 10, (2011) 1863-1869 [pdf]

[p60]

Projective power entropy and maximum Tsallis entropy distributions. S. Eguchi, O. Komori and S. Kato. Entropy 13, 10 (2011) 1746-1764. [online]

[p59]

A boosting method for maximizing the partial area under the ROC curve. O. Komori and S. Eguchi.  BMC Bioinformatics 11:314 (2010). [online]

[p58]

Robust QTL analysis by minimum $beta$-divergence method. M. N. H. Mollah and S. Eguchi.  International Journal of Data Mining and Bioinformatics, 4, 4 (2010) 471-485 [pdf]

[p57]

AUC maximization method in credit scoring. K. Miura, S. Yamashita and S. Eguchi. J. Risk Model Validation, 4, 2 (2010) 3-25. [preprint]

[p56]

Entropy and divergence associated with power function and the statistical application. S. Eguchi and S. Kato. Entropy 12, 2 (2010) 262-274.  [online]

[p55]

Robust extraction of local structures by the minimum beta-divergence method. N. H. Mollah, N. Sultana, M. Minami and  S. Eguchi. Neural Networks 23, 2 (2010) 226-238.  [preprint]

[p54]

Likelihood for statistically equivalent models. J. Copas and S. Eguchi. J. Royal Statistical Society B, 72, 2 (2010) 193-217. [preprint]

[p53]

Maximum regularized likelihood estimator of finite mixtures with a structural model.  S. Eguchi and K. Yoshioka. Communications in Statistics 39: 8 (2010) 1498-1510. [preprint]

[p52]

Robust kernel principal component analysis.  S-Y. Huang, Y-R. Yeh and S. Eguchi. Neural Computation, 21, 11 (2009) 3179-3213. [preprint]

[p51]

SNEP: Simultaneous detection of nucleotide and expression polymorphisms using Affymetrix GeneChip. H. Fujisawa, Y. Horiuchi, Y. Harushima, T. Takada, S. Eguchi, T. Mochizuki, T. Sakaguchi, T. Shiroishi, and N. Kurata.  BMC Bioinformatics (2009) 10: 131. [online]

[p50]

Boosting method for local learning in statistical pattern recognition. M. Kawakita and S. Eguchi. Neural Computation, 20, 11 (2008) 2792-2838. [preprint]

[p49]

Robust parameter estimation with a small bias against heavy contamination. H. Fujisawa and S. Eguchi. J. Multivariate Analysis, 99, 9 (2008) 2053-2081. [preprint]

[p48]

Robust boosting algorithm against mislabeling in multi-class problems. T. Takenouchi, S. Eguchi, N. Murata and T. Kanamori.  Neural Computation 20, 6 (2008) 1596-1630. [abst] [preprint]   

[p47]

Asymptotical improvement of maximum likelihood estimators on Kullback-Leibler loss. S. Eguchi and T. Yanagimoto. J. Statist. Plan. Infer. 138, 11 (2008) 3502-3511. [abst] [preprint]

[p46]

Common peak approach using mass spectrometry data sets for predicting the effects of anticancer drugs on breast cancer. M. Ushijima, S. Miyata, S. Eguchi, M. Kawakita, M. Yoshimoto, T. Iwase, F. Akiyama, G. Sakamoto, K. Nagasaki, Y. Miki, T. Noda, Y. Hoshikawa and M. Matsuura. Cancer Informatics, 3 (2007) 285-293. [abst] [preprint]

[p45]

Importance sampling via the estimated sampler. M. Henmi, R. Yoshida and S. Eguchi. Biometrika 94, 4 (2007)  985-991 . [abst] [preprint]

[p44]

Identifying haplotype block structure by using ancestor-derived model. H. Fujisawa, M. Isomura, S. Eguchi, M. Ushijima, S. Miyata, Y. Miki, M. Matsuura. J. Human Genetics 52, 9 (2007) 738-746. [abst] [preprint]

[p43]

Robust loss functions for boosting. T. Kanamori, T. Takenouchi, S. Eguchi and N. Murata. Neural Computation, 19, 8 (2007) 2183-2244. [abst] [preprint]

[p42]

Confidence intervals and P-values for meta analysis with publication bias. M. Henmi, J. Copas and S. Eguchi. Biometrics, 63, 2 (2007) 475-482. [abst] [preprint]

[p41]

Robust prewhitening for ICA by minimizing beta-divergence and its application to FastICA. M. N. H. Mollah, M. Minami and S. Eguchi. Neural Processing Letters, 25, 2 (2007) 91-110. [abst] [preprint]

[p40]

GroupAdaBoost: accurate prediction and selection of important genes. T. Takenouchi, M. Ushijima and S.Eguchi. IPSJ Transactions on Bioinformatics 3 (2007) 1-8. [abst] [preprint]

[p39]

Identification of biomarkers from mass spectrometry data using a "common" peak approach. T. Fushiki, H. Fujisawa and S. Eguchi. BMC Bioinformatics (2006) 7: 358. [abst] [preprint]

[p38]

Interpreting Kullback-Leibler divergence with the Neyman-Pearson lemma.  S. Eguchi and J. Copas. J. Multivariate Analysis, 97, 9 (2006) 2034-2040. [abst] [preprint]

[p37]

Image classification based on Markov random field models with Jeffreys divergence. R. Nishii and S. Eguchi. J. Multivariate Analysis, 97, 9 (2006) 1997-2008. [abst] [preprint]

[p36]

Exploring latent structure of mixture ICA models by the minimum beta-divergence method.   M. N. H. Mollah, M. Minami and S. Eguchi. Neural Computation, 18, 1 (2006) 166-190. [abst] [preprint]

[p35]

Robust estimation in the normal mixture model. H. Fujisawa and S. Eguchi. J. Statist. Plan. Infer., 136, 11 (2006) 3989-4011. [abst] [preprint]

[p34]

Information geometry and statistical pattern recognition. S. Eguchi. Sugaku Expositions, Amer. Math. Soc, 19 (2006) 197-216. [abst] [preprint]

[p33]

Local likelihood density estimation when the bandwidth is large. B. U. Park, Y. K. Lee, T. Y. Kim, C. Park and S. Eguchi. J. Statist. Plan. Infer., 136, 3 (2006) 839-859.  [abst] [preprint]

[p32]

An introduction to the predictive technique AdaBoost with a comparison to generalized additive models. M. Kawakita, M. Minami, S. Eguchi and C. E. Lennert-Cody.  Fisheries Research, 76, 3 (2005) 328-343 [abst] [preprint]

[p31]

Supervised image classification by contextual AdaBoost based on posteriors in neighborhoods. R. Nishii and S. Eguchi. IEEE Tran. on Geoscience and Remote Sensing, 43, 11 (2005) 2547-2554. [abst] [preprint]

[p30]

Local model uncertainty and incomplete data bias (with discussion). J. Copas and S. Eguchi. J. Royal Statistical Society B, 67, 4 (2005) 459-513. [abst] [preprint]

[p29]

Modeling late entry bias in survival analysis.   M. Matsuura and S. Eguchi. Biometrics, 61, 2 (2005) 559-566. [abst] [preprint]

[p28]

Local likelihood regression of acoustic logging data with adaptive selection of multiple bandwidth.   S. Watanabe, M. Minami and S. Eguchi. Geophisical Explanation, 57, 5 (2004) 535-544. [abst] [preprint]

[p27]

A paradox concerning nuisance parameters and projected estimating functions. M. Henmi and S. Eguchi.  Biometrika, 91, 4 (2004) 929-941. [abst] [preprint]  

[p26]

Robust principal component analysis with adaptive selection for tuning parameters.   I. Higuchi and S. Eguchi. J. Machine Learning Research, 5 (2004) 453-471. [abst] [preprint]  

[p25]

Information geometry of U-Boost and Bregman divergence.  N. Murata, T. Takenouchi, T. Kanamori and S. Eguchi. Neural Computation, 16, 7 (2004) 1437-1481.   [abst] [preprint]

[p24]

Genotyping of single nucleotide polymorphism using model-based clustering.  H. Fujisawa, S. Eguchi, M. Ushijima, S. Miyata, Y. Miki, T. Muto and M. Matsuura. Bioinformatics, 20, 5 (2004) 718-726.  [abst] [preprint] 

[p23]

Robustifying AdaBoost by adding the naive error rate.  T. Takenouchi and S. Eguchi.  Neural Computation, 16, 4 (2004) 767-787. [abst] [preprint]

[p22]

Local likelihood method: a bridge over parametric and nonparametric regression.  S. Eguchi, T-Y. Kim and B. U. Park.  J. Nonparametric Statistics, 15, 6 (2003) 665-683.   [abst] [preprint]

[p21]

Robust blind source separation by beta-divergence. M. Minami and S. Eguchi, Neural Computation, 14, 8 (2002) 1859-1886.  [abst] [preprint]

[p20]

A class of logistic-type discriminant functions. S. Eguchi and J. Copas, Biometrika, 89, 1 (2002) 1-22.  [abst] [preprint]

[p19]

Local sensitivity approximation for selectivity bias. J. Copas and S. Eguchi, J. Royal Statistical Society B, 63, 4 (2001) 871-895.  [abst] [preprint]

[p18]

A class of robust principal component vectors.   H. Kamiya and S. Eguchi, J. Multivariate Analysis, 77, 2 (2001) 239-269.  [abst] [preprint]

[p17]

Recent developments in discriminant analysis from an information geometric point of view.  J. Korean Statist. Soc. 30 (2001) 247-264.  S. Eguchi and J. Copas. [abst] [preprint]

[p16]

A comparison of methods for estimating individual pharmacokinetic parameters.  T. Amisaki and S. Eguchi,  J. Pharmacokinetics and Biopharmaceutics, 27, 1 (1999) 103-121.  [abst] [preprint]

[p15]

A class of local likelihood methods and near-parametric asymptotics. S. Eguchi and J. Copas, J. Royal Statistical Society B, 60, 4 (1998) 709-724.  [abst] [preprint]

[p14]

The influence function of principal component analysis by self-organizing rule. I. Higuchi and S. Eguchi, Neural Computation, 10, 6 (1998) 1435-1444. [abst] [preprint]

[p13]

Pharmacokinetic parameter estimations by minimum relative entropy method. T. Amisaki and S. Eguchi,  J. Pharmacokinetics and Biopharmaceutics, 23, 5 (1995) 479-494. [abst] [preprint]

[p12]

Further discussion of second order efficiency for estimation. S. Eguchi. Questio 17 (1993) 347-364.  [abst] [pdf]

[p11]

Geometry of minimum contrast. S. Eguchi. Hiroshima Math, 22, 3 (1992) 631-647.[pdf]

[p10]

The projection method for accelerated life test model in bivariate exponential distributions. S. Eguchi. Hiroshima Math. J., 22, 1 (1992) 185-193. [pdf]

[p09]

A geometric look at nuisance parameter effect of local powers in testing hypothesis. S. Eguchi. Ann. Inst. Statist. Math,. 43, 2 (1991) 245-260. [abst] [pdf]

[p08]

Testing the Hardy-Weinberg equilibrium in the HLA system.  S. Eguchi and M. Matsuura,  Biometrics, 46, 2 (1990) 415-426. [abst]  [pdf]  

[p07]

Estimation of gene frequency and test for Hardy-Weinberg equilibrium in the HLA system.  M. Matsuura  and S. Eguchi, Environmental Health Perspectives, 87 (1990) 149-155.  [abst] [pdf]

[p06]

A class of tests for general covariance structure.  H. Wakaki, S. Eguchi and Y. Fujikoshi. J. Multivariate Analysis, 32, 2 (1990) 313-325.   [abst] [pdf]

[p05]

A unified approach to improper solutions of maximum likelihood estimates. S. Eguchi. J. Japan Statist. Soc. 19 (1989) 67-82. [abst] [pdf]

[p04]

A projection method of estimation for a subfamily of exponential families. S. Eguchi. Ann. Inst. Statist. Math. 38 A, 1 (1986) 385-398. [pdf]

[p03]

A differential geometric approach to statistical inference on the basis of contrast functionals. S. Eguchi. Hiroshima Math. J., 15, 2 (1985) 341-391. [abst] [pdf]

[p02]

A characterization of second order efficiency in a curved exponential family. S. Eguchi. Ann. Inst. Statist. Math., 36 A, 1 (1984) 199-206. [pdf]

[p01]

Second order efficiency of minimum contrast estimators in a curved exponential family. S. Eguchi. Ann Statist., 11, 3 (1983) 793-803. [abst] [pdf]