Hiroshima Statistical Research Group: Technical Report

(Last Update:(2025.3.17)

2025 / 2024 / 2023 / 2022 / 2021 / 2020 / 2019 / 2018 / 2017
2016 / 2015 / 2014 / 2013 / 2012 / 2011 / 2010 / 2009 / 2008 / 2007 / 2006 / 2005

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2025 >>
25-01	A Modified KOO Method for Selection of Variables in Large-dimensional Regression and Estimation of its Selection Probability by T. Sakurai, T. Yamada and Y. Fujikoshi
25-02	Multi-sample problem in sphericity test with monotone missing data by T. Sato, A. Yagi and T. Seo
2024 >>
24-01	An Asymptotic Expansion of the Null Distribution for Sphericity Test Statistic with Monotone Missing Data by T. Sato, A. Yagi and T. Seo
24-02	Generalized Fused Lasso for Grouped Data in Generalized Linear Models by M. Ohishi
24-03	On the Extension of Test Statistics for the Sub-mean Vector under Two-step Monotone Missing Data by R. Hosonuma, T. Kawasaki and T. Seo
24-04	A fast and consistent variable selection method for conditional independence under large-dimensional Gaussian case by T. Yamada, T. Sakurai and Y. Fujikoshi
24-05	Consistent Model Selection Methods Using Wald Statistics and Estimation of Selection Probability by T. Sakurai, Y. Fujikoshi and T.Yamada
24-06	Low dimensional factor model-based tests for assessing vector correlation in high-dimensional settings by M. Hyodo, T. Nishiyama and S. Narita
2023 >>
23-01	A Modified Normalizing Transformation Statistic Based on Kurtosis for Testing Multivariate Normality - Empirical Power - by E. Kurita, T. Seo and Z. Hanusz
23-02	Tests for One and Two Mean Vectors and Simultaneous Confidence Intervals with Monotone Incomplete Data by A. Yagi and T. Seo
23-03	A Multivariate Normality Test Based on Kurtosis with Three-step Monotone Missing Data by E. Kurita and T. Seo
23-04	KOO Approach for Scalable Variable Selection Problem in Large-dimensional Regression by Z. Bai, K.P Choi, Y. Fujikoshi and J. Hu
23-05	Estimation of Spatial Effects by Generalized Fused Lasso for Nonuniformly Sampled Spatial Data: An Analysis of the Body Condition of Common Minke Whales (Balaenoptera acutorostrata acutorostrata) in the Northeast Atlantic by M. Yamamura, H. Yanagihara, M. Ohishi, K. Fukui, H. Solvang, N. Øien and T. Haug
23-06	Tests for Multivariate Kurtosis with Two- and Three-Step Monotone Missing Data by E. Kurita and T. Seo
2022 >>
22-01	A Behrens-Fisher problem for general factor models in high dimensions by M. Hyodo, T. Nishiyama and T. Pavlenko
22-02	A modified normalizing transformation statistic based on kurtosis for multivariate normality testing by E. Kurita, T. Seo and Z. Hanusz
22-03	Confidence Intervals in Multiple Linear Regression Conditioned on the Selected Model via the Kick-One-Out Method by K. Mochizuki and H. Yanagihara
22-04	Testing Equality of Multivariate Normal Populations with Three-step Monotone Missing Data by R. Sakai, A. Yagi and T. Seo
22-05	Stable Estimation of the Slant Parameter in Skew Normal Regression via an MM Algorithm and Ridge Shrinkage by M. Ohishi, H. Yanagihara, H. Wakaki and M. Ono
22-06	High-Dimensional Consistencies of KOO Methods for Selecting Graphical Models by Y. Fujikoshi, T. Sakurai and T. Yamada
22-07	High-Dimensional Consistencies of KOO Methods for Selection of Variables in Multivariate Linear Regression Models with Covariance Structures by Y. Fujikoshi and T. Sakurai
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
21-04	Simultaneous Testing of Mean Vector and Covariance Matrix with Three-step Monotone Missing Data by R. Sakai, A. Yagi and T. Seo
21-05	Multivariate normality test based on kurtosis with two-step monotone missing data by E. Kurita and T. Seo
21-06	Coordinate Descent Algorithm of Generalized Fused Lasso Logistic Regression for Multivariate Trend Filtering by M. Ohishi, M. Yamamura and H. Yanagihara
21-07	On model selection consistency using a kick-one-out method for selecting response variables in high-dimensional multivariate linear regression by R. Oda H. Yanagihara and Y. Fujikoshi
21-08	An l_{2,0}-norm constrained matrix optimization via extended discrete first-order algorithms by R. Oda, M. Ohishi, Y. Suzuki and H. Yanagihara
21-09	High-dimensional consistencies of KOO methods in multivariate regression model and discriminant analysis by Y. Fujikoshi
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.