Hiroshima Statistical Research Group: Technical Report

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2021 / 2020 / 2019 / 2018 / 2017
2016 / 2015 / 2014 / 2013 / 2012 / 2011 / 2010 / 2009 / 2008 / 2007 / 2006 / 2005

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2021 >>
21-01	Optimizations for Categorizations of Explanatory Variables in Linear Regression via Generalized Fused Lasso by M. Ohishi, K. Okamura, Y. Itoh and H. Yanagihara
21-02	Coordinate Descent Algorithm for Generalized Group Fused Lasso by M. Ohishi, K. Okamura, Y. Itoh and H. Yanagihara
21-03	High-dimensional Multiple Comparison Procedures among Mean Vectors under Covariance Heterogeneity by M. Hyodo, T. Nishiyama, H. Hayashi
2020 >>
20-01	NON-ASYMPTOTIC ANALYSIS OF APPROXIMATIONS FOR LAWLEY-HOTELLING AND BARTLETT-NANDA-PILLAI STATISTICS IN HIGH-DIMENSIONAL SETTINGS by A. A. Lipatiev and V. V. Ulyanov
20-02	Asymptotic optimality of Cp-type criteria in high-dimensional multivariate linear regression models by S. Imori
20-03	High-dimensionality-adjusted Asymptotically Loss and Mean Efficient GCp Criterion for Normal Multivariate Linear Regression Models by H. Yanagihara
20-04	Modified Likelihood Ratio Test for Simultaneous Testing of Mean Vectors and Covariance Matrices with Missing Data by R. Nomura, A. Yagi and T. Seo
20-05	Exact and approximate computation of critical values of largest root test in high dimension by G. A. T. Xiang, Z. Bai, K. P. Choi, Y. Fujikoshi and J. Hu
20-06	Contributions to Multivariate Analysis due to C. R. Rao and Associated Developments by Y. Fujikoshi
20-07	Ridge Parameters Optimization based on Minimizing Model Selection Criterion in Multivariate Generalized Ridge Regression by M. Ohishi
20-08	A Consistent Likelihood-Based Variable Selection Method in Normal Multivariate Linear Regression by R. Oda and H. Yanagihara
20-09	AIC for Growth Curve Model with Monotone Missing Data by A. Yagi, T. Seo and Y. Fujikoshi
2019 >>
19-01	A fast and consistent variable selection method for high-dimensional multivariate linear regression with a large number of explanatory variables by R. Oda and H. Yanagihara
19-02	Strong consistency of log-likelihood-based information criterion in high-dimensional canonical correlation analysis by R. Oda, H. Yanagihara and Y. Fujikoshi
19-03	Growth Curve Model with Bilinear Random Coefficients by S. Imori, D. von Rosen and R. Oda
19-04	A consistent variable selection method in high-dimensional canonical discriminant analysis by R. Oda, Y. Suzuki, H. Yanagihara and Y. Fujikoshi
19-05	Equivalence between Adaptive-Lasso and Generalized Ridge Estimators in Linear Regression with Orthogonal Explanatory Variables after Optimizing Regularization Parameters by M. Ohishi, H. Yanagihara and S. Kawano
19-06	Computable Error Bounds for Asymptotic Approximations of the Quadratic Discriminant Function by Y. Fujikoshi
19-07	Estimation for Spatial Effects by Using the Fused Lasso by M. Ohishi, K. Fukui, K. Okamura, Y. Itoh and H. Yanagihara
19-08	Maximum Likelihood Estimators in Growth Curve Model with Monotone Missing Data by A. Yagi, T. Seo and Y. Fujikoshi
2018 >>
18-01	Constrained linear discriminant rule for 2-groups via the Studentized classification statistic W for large dimension by T. Yamada
18-02	Moment matching priors for non-regular models by S. Hashimoto
18-03	T^2 Type Test Statistic and Simultaneous Confidence Intervals for Sub-mean Vectors in k-sample Problem by T. Naito, T. Kawasaki and T. Seo
18-04	Consistency of Test-based Criterion for Selection of Variables in High-dimensional Two Group-Discriminant Analysis. by Y. Fujikoshi and T. Sakurai
18-05	Consistency of Distance-based Criterion for Selection of Variables in High-dimensional Two-Group Discriminant Analysis. by T. Sakurai and Y. Fujikoshi
18-06	A Review of Discriminant Analysis by Regression Approach by Y. Fujikoshi and T. Kan
18-07	Testing Equality of Two Mean Vectors with Monotone Missing Data by A. Yagi, T. Seo and Z. Hanusz
18-08	Testing independence in high-dimensional data:ρV -coefficient based approach by M. Hyodo, T. Nishiyama and T. Pavlenko
18-09	Strong Consistency of the AIC, BIC, Cp and KOO Methods in High-Dimensional Multivariate Linear Regression by Z. Bai, Y. Fujikoshi and J. Hu
18-10	A high-dimensional bias-corrected AIC for selecting response variables in multivariate calibration by R. Oda , Y. Mima, H. Yanagihara and Y. Fujikoshi
2017 >>
17-01	Reference priors via α-divergence for a certain non-regular multi-parametric model by S. Hashimoto
17-02	Asymptotic Expansions for Scale Mixtures of F-Distribution and Their Error Bounds by Y. Fujikoshi and R. Shimizu
17-03	Estimation of covariance matrix via shrinkage Cholesky factor by N. Chanohara, T. Nakagawa and H. Wakaki
17-04	Interval estimation in two-group discriminant analysis under heteroscedasticity for large dimension by T. Yamada
17-05	Robust Bayesian inference via γ-divergence by T. Nakagawa and S. Hashimoto
17-06	Simultaneous testing of the mean vector and the covariance matrix for high-dimensional data by M. Hyodo and T. Nishiyama
17-07	A Fast Algorithm for Optimizing Ridge Parameters in a Generalized Ridge Regression by Minimizing an Extended GCV Criterion by M. Ohishi, H. Yanagihara and Y. Fujikoshi
17-08	A Cp type criterion for model selection in the GEE method when both scale and correlation parameters are unknown by Y. Inatsu and T. Sato
17-09	Improved Simplified T^2 Test Statistics for Mean Vector with Monotone Missing Data by A. Yagi, T. Seo and Z. Hanusz
17-10	Estimation of multivariate 3rd moment for high-dimensional data and its application for testing multivariate normality by T. Yamada and T. Himeno
17-11	High-Dimensional Asymptotic Distributions of Simplified MLEs in Growth Curve Model with an Autoregressive Covariance Structure by T. Sakurai, R.Enomoto and Y. Fujikoshi
17-12	High-dimensional asymptotic results for EPMCs of W- and Z- rules by T. Yamada, T. Sakurai and Y. Fujikoshi
17-13	High-Dimensional Properties of Information Criteria and Their Efficient Criteria for Multivariate Linear Regression Models with Covariance Structures by T. Sakurai and Y. Fujikoshi
17-14	Robust estimation of skew-normal distribution with location and scale parameters via log-regularly varying functions by S. Hashimoto
17-15	Second Order Expansions for Distributions of Statistics and Its Quantiles Based on Random Size Samples by G. Christoph, M. M. Monakhov, V. V. Ulyanov
2016 >>
16-01	On the Likelihood Ratio Test for the Equality of Multivariate Normal Populations with Two-step Monotone Missing Data by M. Hosoya and T. Seo
16-02	Simultaneous Testing of Mean Vectors and Covariance Matrices with Monotone Missing Data by A. Yagi, R. Yamaguchi and T. Seo
16-03	Non-Asymptotic Results for Cornish-Fisher Expansions by V.V. Ulyanov, M. Aoshima and Y. Fujikoshi
16-04	Testing Block-Diagonal Covariance Structure for High-Dimensional Data Under Non-normality by Y. Yamada, M. Hyodo and T. Nishiyama
16-05	Temporal and geographical variation in body condition of common minke whales (Balaenoptera acutorostrata acutorostrata) in the Northeast Atlantic. by H. K. Solvang , H. Yanagihara, N. Oien and T. Haug
16-06	Likelihood Ratio Tests in Multivariate Linear Model by Y. Fujikoshi
16-07	Selection of the linear and the quadratic discriminant functions when the difference between two covariance matrices is small by T. Nakagawa and H. Wakaki
16-08	A Modified Likelihood Ratio Test for a Mean Vector with Monotone Missing Data by A. Yagi, T. Seo and M. Srivastava
16-09	High-Dimensional Asymptotic Distributions of Characteristic Roots in Multivariate Linear Models and Canonical Correlation Analysis by Y. Fujikoshi
16-10	Asymptotic non-null distributions of test statistics for redundancy in the high-dimensional canonical correlation analysis by R. Oda, H. Yanagihara and Y. Fujikoshi
16-11	EPMC Estimation in Discriminant Analysis when the Dimension and Sample Sizes are Large by T. Tonda, T. Nakagawa and H. Wakaki
16-12	Consistent information criterion in normal multivariate linear regression models even under high-dimensionality. by H. Yanagihara and H. Shimodaira
16-13	Akaike Information Criterion for ANOVA Model with a Simple Order Restriction by Y. Inatsu
16-14	Model Selection Criteria for ANOVA Model with a Tree Order Restriction by Y. Inatsu
16-15	Bartlett correction to the likelihood ratio test for MCAR with two-step monotone sample by N. Shutoh, T. Nishiyama and M. Hyodo
16-16	Multi-group profile analysis for high-dimensional elliptical populations by M.Hyodo
16-17	Modified Likelihood Ratio Tests in a One-way MANOVA with Monotone Missing Data by A. Yagi, T. Seo and M. Srivastava
2015 >>
15-01	Testing equality of two mean vectors with unequal sample sizes for populations with correlation. by A. Shinozaki, N. Okamoto and T. Seo
15-02	High-Dimensional Consistency of Estimation Criteria for the Rank in Multivariate Linear Model by Y. Fujikoshi and T. Sakurai
15-03	Likelihood ratio test statistic for block compound symmetry covariance structure and its asymptotic expansion. by M. Mitsui, K. Koizumi and T.Seo
15-04	Cut-off point of linear discriminant rule for large dimension. by T. Yamada, T. Himeno and T. Sakurai
15-05	Approximate interval estimation for EPMC for improved linear discriminant rule under high dimensional frame work. by M. Hyodo, T. Mitani, T. Himeno and T. Seo
15-06	Estimation of misclassification probability for a distance-based classifier in high-dimensional data. by Y. Yamada, M. Hyodo and T. Seo
15-07	Tests for Normal Mean Vectors with Monotone Incomplete Data by A. Yagi and T. Seo
15-08	Consistency of log-likelihood-based information criteria for selecting variables in high-dimensional canonical correlation analysis under nonnormality by K. Fukui
15-09	Estimation of misclassification probability for multi-class classification based on the Euclidean distance in high-dimensional data. by M. Hyodo, Y. Yamada and H. Furukawa
15-10	Information Criterion-Based Nonhierarchical Clustering. by I. Nagai, K. Takahashi and H. Yanagihara
15-11	Some Properties of Estimation Criteria for Dimensionality in Principal Component Analysis by Y. Fujikoshiand T. Sakurai
15-12	A likelihood ratio test for subvector of mean vector with two-step monotone missing data by T. Kawasaki and T. Seo
15-13	High-Dimensional Consistency of AIC and BIC for Estimating the Number of Signicant Components in Principal Component Analysis by Z. Bai, Y. Fujikoshi and K. P. Choi
15-14	Asymptotic expansions of the null distribution of the LR test statistic for random-effects covariance structure in a parallel profile model. by Y.Inatsu and H.Wakaki
15-15	Limiting Behavior of Eigenvalues in High-Dimensional MANOVA via RMT by Z. Bai, K.P.Choi and Y.Fujikoshi
2014 >>
14-01	Screening and Selection Methods in High-Dimensional Linear Regression Model by S. Imori, S. Katayama and H. Wakaki
14-02	High-Dimensional Properties of AIC and Cp for Estimation of Dimensionality in Multivariate Models by Y. Fujikoshi
14-03	Bias Correction for T2 Type Statistic with Two-step Monotone Missing Data by T. Kawasaki and T. Seo
14-04	Testing equality of mean vectors based on three-step monotone missing data by A. Yagi and T. Seo
14-05	Consistency properties of AIC, BIC, Cp and their modifications in the growth curve model under a large-(q; n) framework by R. Enomoto, T. Sakurai and Y. Fujikoshi
14-06	Illustration of the Varying Coefficient Model for Analyses the Tree Growth from the Age and Space Perspectives. by M. Yamamura, K. Fukui and H. Yanagihara
14-07	Comparison with RSS-Based Model Selection Criteria for Selecting Growth Functions. by K. Fukui, M. Yamamura and H. Yanagihara
14-08	Simultaneous testing of the mean vector and the covariance matrix with two-step monotone missing data by M. Hosoya and T. Seo
14-09	Tests for Two Mean Vectors and Simultaneous Confidence Intervals for Multiple Comparisons with Three-step Monotone Missing Data by A. Yagi and T. Seo
14-10	High-Dimensional Asymptotic Behaviors of Differences between the Log-Determinants of TwoWishart Matrices by H. Yanagihara, Y. Hashiyama and Y. Fujikoshi
2013 >>
13-01	On Properties of QIC in Generalized Estimating Equations by S. Imori
13-02	Testing linear hypotheses of mean vectors for high-dimension data with unequal covariance matrices by T. Nishiyama, M. Hyodo, T. Seo and T. Pavlenko
13-03	Measures of multivariate skewness and kurtosis in high-dimensional framework by T. SUMIKAWA, K. KOIZUMI, T. SEO
13-04	Optimization using Cross-Validation for Penalized Nonlinear Canonical Correlation Analysis by I. Nagai
13-05	Estimation of the large covariance matrix with two-step monotone missing data by M. Hyodo, N. Shutoh, T. Seo, and T. Pavlenko
13-06	Testing the block-diagonal covariance structure for high-dimensional data by M. Hyodo, N. Shutoh, T. Nishiyama, and T. Pavlenko
13-07	Explicit solution to the minimization problem of generalized cross-validation criterion for selecting ridge parameters in generalized ridge regression by H. Yanagihara
13-08	A Study on the Bias-Correction Effect of the AIC for Selecting Variables in Normal Multivariate Linear Regression Models under Model Misspecification by H. Yanagihara, K. Kamo, S. Imori & M. Yamamura
13-09	Predictive Model Selection Criterion in Generalized Linear Models by S. Imori, K. Satoh and K. Kamo
13-10	Model selection criterion based on the prediction mean squared error in generalized estimating equations by Y. Inatsu and S. Imori
13-11	Conditions for Consistency of a Log-Likelihood-Based Information Criterion in Normal Multivariate Linear Regression Models under the Violation of Normality Assumption by H. Yanagihara
13-12	Consistency of AIC and its modication in the growth curve model under a large-(q; n) framework by R. Enomoto, T. Sakurai and Y. Fujikoshi
13-13	Testing homogeneity of mean vectors under heteroscedasticity in high-dimension by T. Yamada and T. Himeno
13-14	A Test for Mean Vector and Simultaneous Condence Intervals with Three-step Monotone Missing Data by A. Yagi and T. Seo
2012 >>
12-01	Multiple comparisons among mean vectors when the dimension is larger than the total sample size by M. Hyodo, S. Takahashi and T. Nishiyama
12-02	On the distribution of test statistic using Song's kurtosis by R. Enomoto, N. Okamoto and T. Seo
12-03	Bias-corrected aic for selecting variables in multinomial logistic regression models by H. Yanagihara, K. Kamo, S. Imori and K. Satoh
12-04	Selection of Model Selection Criteria for Multivariate Ridge Regression by I. Nagai
12-05	General Formula of Bias-Corrected AIC in Generalized Linear Models with Unknown Scale Parameter by S. Imori
12-06	Asymptotic distribution of the likelihood ratio test statistic for equality of two covariance matrices with two-step monotone missing data by Y. Fukumoto, N. Shutoh and T. Seo
12-07	Asymptotic expansion for the distribution of Wald's classification statistic with two-step monotone missing data by K. Kurihara, R. Enomoto and N. Shutoh
12-08	A Consistency Property of the AIC for Multivariate Linear Models When the Dimension and the Sample Size are Large by H. Yanagihara, H. Wakaki and Y. Fujikoshi
12-09	Principal Components Regression by using Generalized Principal Components Analysis by M. Fujiwara, T. Minamidani, I. Nagai and H. Wakaki
12-10	Jackknife Bias Correction of the AIC for Selecting Variables in Canonical Correlation Analysis under Model Misspecification by Y. Hashiyama, H. Yanagihara and Y. Fujikoshi
12-11	Estimations for some functions of covariance matrix in high dimension under non-normality by T. Himeno and T. Yamada
12-12	Profile analysis in high-dimensional data by N. Shutoh and S. Takahashi
12-13	High-Dimensional AICs for Selection of Redundancy Models in Discriminant Analysis by T. Sakurai, T. Nakada and Y. Fujikoshi
12-14	High-dimensional AIC and consistency properties of several criteria in multivariate linear regression by by Y. Fujikoshi, T. Sakurai and H. Yanagihara
12-15	Choosing the Number of Repetitions in the Multiple Plug-in Optimization Method for the Ridge Parameters in Multivariate Generalized Ridge Regression by I. Nagai, K. Fukui and H. Yanagihara
12-16	High-Dimensional AIC in the Growth Curve Model by Y. Fujikoshi, R. Enomoto and T. Sakurai
12-17	Test for assessing multivariate normality which is available for high-dimensional data by T. Yamada and T. Himeno
12-18	Multiple comparison procedures for high-dimensional data and their robustness under non-normality by S. Takahashi, M. Hyodo, T. Nishiyama and T. Pavlenko
12-19	A Two Sample Test for Mean Vectors with Unequal Covariance Matrices by T. Kawasaki and T. Seo
12-20	Computable error bounds for high{dimensional approximations of LR test for additional information in canonical correlation analysis by H. Wakaki and Y. Fujikoshi
2011 >>
11-01	Testing independence by step-wise multiple comparison procedure by S. Takahashi, T. Nishiyama and T. Seo
11-02	Normal Approximation to Multivariate Sample Measures of Kurtosis by A. Hara and T. Seo
11-03	A New Multivariate Kurtosis and Its Asymptotic Distribution by C. Miyagawa and T. Seo
11-04	Selecting a shrinkage parameter in structural equation modeling with a near singular covariance matrix by the GIC minimization method by A. Kamada
11-05	Modified Cp Criterion for Optimizing Ridge and Smooth Parameters in the MGR Estimator for the Nonparametric GMANOVA model by I. Nagai
11-06	General formula of bias-corrected AIC in gereralized linear models. by S. Imori, H. Yanagihara and H. Wakaki
11-07	Pairwise comparisons among components of mean vector in elliptical distributions by S. Takahashi, T. Nishiyama and T. Seo
11-08	An asymptotic approximation for EPMC in linear discriminant analysis based on three-step monotone missing data by K. Kurihara, N. Shutoh and T. Seo
2010 >>
10-01	Asymptotic expansion of the distribution of the studentized linear discriminant function with 2-Step monotone missing data by N. Shutoh and T. Seo
10-02	Asymptotics and bootstrap inference for panel quantile regression models with fixed effects by K. Kato, A. F. Galvao, Jr. and G. V. Montes-Rojas
10-03	Optimization of Ridge Parameters in Multivariate Generalized Ridge Regression by Plug-in Methods by I. Nagai, H. Yanagihara and K. Satoh
10-04	Asymptotic expansions relating to discrimination based on 2-step monotone missing samples by N. Shutoh
10-05	Asymptotic expansions for a class of tests for a general covariance structure under a local alternative by H. Shimizu and H. Wakaki
10-06	Approximation to the upper percentiles of the statistic for pairwise comparison among components of mean vector in elliptical distributions by S. Takahashi, T. Nishiyama and T. Seo
10-07	On the distribution of test statistic using Srivastava's skewness and kurtosis by R. Enomoto, N. Okamoto and T. Seo
10-08	Tests for mean vector and simultaneous confidence intervals with two-step monotone missing data by N. Seko, A. Yamazaki and T. Seo
10-09	Constrained sample discrimination with the Studentized linear discriminant function based on monotone missing training data by N. Shutoh
10-10	On the conservative multivariate multiple comparison procedure of correlated mean vectors with a control by T. Nishiyama
2009 >>
09-01	Expected probabilities of misclassification in linear discriminant analysis based on 2-Step monotone missing samples by N. Shutoh, M. Hyodo and T. Seo
09-02	Asymptotic normality of Powell's kernel estimator by K. Kato
09-03	Weighted Nadaraya-Watson estimation of conditional expected shortfall by K. Kato
09-04	Bias-corrected AIC for selecting variables in Poisson regression models by K. Kamo, H. Yanagihara and K. Satoh
09-05	Estimation of the innovation density in nonlinear autoregressive models with applications by K. Kato
09-06	Improvement of the Quality of the Chi-square Approximation for the ADF Test on a Covariance Matrix with a Linear Structure by C. Matsumoto, H. Yanagihara and H. Wakaki
09-07	A Derivative-free Multivariate Function Maximization Algorithm and Its Application to Maximum Likelihood by T. Akita, S. Izumi and M. Ohtaki
09-08	A Non-iterative Optimization for Smoothness in Penalized Spline Regression by H. Yanagihara
2008 >>
08-01	On the Distribution of Multivariate Sample Skewness for Assessing Multivariate Normality by N. Okamoto and T. Seo
08-02	Testing equality of two mean vectors and simultaneous confidence intervals in repeated measures with missing data by K. Koizumi and T. Seo
08-03	Iterative Bias Correction of the Cross-Validation Criterion by H. Yanagihara and H. Fujisawa
08-04	An Unbiased Cp Criterion for Multivariate Ridge Regression by H. Yanagihara and K. Satoh
08-05	Edgeworth Expansions of Functions of the Sample Covariance Matrix with an Unknown Population by H. Yanagihara and K. H. Yuan
08-06	Asymptotic expansions of test statistics for dimensionality and additional information in canonical correlation analysis when the dimension is large by T. Sakurai
08-07	Simultaneous confidence intervals among k mean vectors in repeated measures with missing data by K. Koizumi and T. Seo
08-08	Estimation of varying coefficients for a growth curve model by K. Satoh and H. Yanagihara
08-09	On approximation of goodness-of-fit statistics for discrete three dimensional data by Zh. A. Assylbekov, V. V. Ulyanov and V. N. Zubov
08-10	Chi-squared approximation for the power divergence family of statistics by V. N. Zubov and V. V. Ulyanov
08-11	Numerical Studies on Convergence of Multinomial Goodness-of-fit Statistics to Chisquare Distribution by Zh. Assylbekov
08-12	A nonparametric method of multi-step ahead forecasting in diffusion processes by M. Yamamura and I. Shoji
08-13	Variable Selection in Multivariate Linear Regression Models with Fewer Observations than the Dimension by M. Yamamura, H. Yanagihara and M. Srivastava
08-14	On Jarque-Bera tests for assessing multivariate normality by K. Koizumi, N. Okamoto and T. Seo
2007 >>
07-01	A Class of Model Selection Criteria Based on Cross-Validation Method by H. Yanagihara, K. H. Yuan, H. Fujisawa and K. Hayashi
07-02	Ordering Municipalities by Medical Cost Efficiency Under the Japanese National Health Insurance System using the Stochastic Cost Frontier Model by M. Yamamura and H. Yanagihara
07-03	An error bound for high-dimensional Edgeworth expansion of Wilks' Lambda distribution by H. Wakaki
07-04	Error bounds for high-dimensional Edgeworth expansions for some tests on covariance matrices by H. Wakaki
07-05	A Discriminant Condition for the Test of Greatest Power in the MANOVA Model When the Dimension is Large Compared to the Sample Size by T. Himeno
07-06	The statistic of greatest power in a class of test statistics for testing equality of means of two groups without assuming equal covariance matrices by T. Himeno
07-07	GLS Discrepancy Based Information Criteria for Selecting Covariance Structure Models by H. Yanagihara, T. Himeno and K. H. Yuan
07-08	Analysis of Grouped Growth Patterns in Even-Aged Sugi Forest Stand within the Framework of Mixture Model by H. Yanagihara, Y. Ninomiya and A. Yoshimoto
2006 >>
06-01	Second-Order Bias-Corrected AIC in Multivariate Normal Linear Models under Nonnormality by H. Yanagihara, K. Kamo and T. Tonda.
06-02	A mathematical estimation of cancer incidence using data from population-based cancer registries by K. Kamo, S. Kaneko, K. Satoh, H. Yanagihara, S. Mizuno and T. Sobue.
06-03	Conditions for Robustness to Nonnormality of Test Statistics in a GMANOVA Model. by H. Yanagihara.
06-04	On the Distribution of Kurtosis Test for Multivariate Normality by T. Seo and M. Ariga
06-05	Computable Error Bounds for Approximations of Transformed Chi-Squared Variables and Its Statistical Applications. by V. V. Ulyanov, G. Christoph and Y. Fujikoshi
06-06	A Class of Population Covariance Matrices for Monte Carlo Simulation by K. H. Yuan, K. Hayashi and H. Yanagihara
06-07	The multivariate tukey-kramer multiple comparison procedure among four correlated mean vectors by T. Seo and T. Nishiyama
2005 >>
05-01	Bias Correction of Cross-Validation Criterion Based on Kullback-Leibler Information under a General Condition. by H. Yanagihara, T. Tonda and C. Matsumoto.
05-02	Nonparametric Kernel Regression for Multidimensional Data by H. Okumura and K. Naito.
05-03	Multivariate Analysis of Variance with fewer observations than the dimension by M. S. Srivastava and Y. Fujikoshi.
05-04	On the conservative multivariate Tukey-Kramer type procedures for multiple comparisons among mean vectors by T. Seo and T. Nishiyama.
05-05	On simultaneous confidence intervals for all contrasts in the means of the intraclass correlation model with missing data by T. Seo, J. Kikuchi and K. Koizumi.
05-06	Prediction Error Criterion for Selecting of Variables in Regression Model by Y. Fujikoshi, T. Kan and S. Takahashi.