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JSS Research Series in Statistics

日本統計学会では，2015年から，日本統計学会JSS-springer委員会編集によるSpringer社の英文 書籍の シリーズJSS Research Series in Statisticsを刊行しております。（１冊50～125ページの小冊子） 本シリーズでの書籍の刊行を希望される会員の方は、こちらをご覧下さい。

詳細はSpringer社ホームページ（http://www.springer.com/series/13497）をご覧下さい。

既刊タイトル（2024年9月現在）

• Maruyama, Y., Kubokawa, T., Strawderman, W. E. (2023). Stein Estimation, Springer, ISBN 978-981-99-6076-7.
• Goto, Y., Nagahata, H., Taniguchi, M., Monti, A. C., Xu, X. (2023). ANOVA with Dependent Errors, Springer, ISBN 978-981-99-4171-1.
• Rizky Reza Fauzi, Maesono, Y. (2023). Statistical Inference Based on Kernel Distribution Function Estimators, Springer, ISBN 978-981-99-1861-4.
• Takahashi, M., Omori, Y., Watanabe, T. (2023). Stochastic Volatility and Realized Stochastic Volatility Models, Springer, ISBN 978-981-99-0934-6.
• Sugasawa, S., Kubokawa, T. (2023). Mixed-Effects Models and Small Area Estimation, Springer, ISBN 978-981-19-9485-2.
• Shimizu S. (2022). Statistical Causal Discovery: LiNGAM Approach, Springer, ISBN 978-4-431-55783-8
• Shiraishi T. (2022). Multiple Comparisons for Bernoulli Data, Springer, ISBN 978-981-19-2707-2.
• Muroi Y. (2022). Computation of Greeks Using the Discrete Malliavin Calculus and Binomial Tree, Springer, ISBN 978-981-19-1072-2.
• Shimizu, Y. (2022). Asymptotic Statistics in Insurance Risk Theory, Springer, ISBN 978-981-16-9284-0.
• Akashi, F., Taniguchi, M., Monti, A.C., Amano, T. (2021). Diagnostic Methods in Time Series, Springer, ISBN 978-981-16-2264-9.
• Hoshino, N., Mano, S., Shimura, T. (2021). Pioneering Works on Extreme Value Theory: In Honor of Masaaki Sibuya, Springer, ISBN 978-981-16-0767-7.
• Hoshino, N., Mano, S., Shimura, T. (2020). Pioneering Works on Distribution Theory: In Honor of Masaaki Sibuya, Springer, ISBN 978-981-15-9662-9.
• Yamato, H. (2020). Statistics Based on Dirichlet Processes and Related Topics, Springer, ISBN 978-981-15-6975-3.
• Sun, L.-H., Huang, X.-W., Alqawba, M.S., Kim, J.-M., Emura, T. (2020). Copula-Based Markov Models for Time Series, Springer, ISBN 978-981-15-4998-4.
• Fujikoshi, Y., Ulyanov V., V. (2020). Non-Asymptotic Analysis of Approximations for Multivariate Statistics, Springer, ISBN 978-981-13-2616-5.
• Tsukuma, H., Kubokawa, T. (2020). Shrinkage Estimation for Mean and Covariance Matrices, Springer, ISBN 978-981-15-1596-5.
• Miyawaki, K. (2019). Bayesian Analysis of Demand Under Block Rate Pricing, Springer, ISBN 978-981-15-1857-7.
• Shiraishi, T., Sugiura, H., Matsuda, S. (2019). Pairwise Multiple Comparisons, Springer, ISBN 978-981-15-0066-4.
• Sawa, M., Hirao, M., Kageyama, S. (2019). Euclidean Design Theory, Springer, ISBN 978-981-13-8075-4.
• Komori, O., Eguchi, S. (2019). Statistical Methods for Imbalanced Data in Ecological and Biological Studies, Springer, ISBN 978-4-431-55570-4.
• Daimon, T., Hirakawa, A., Matsui, S. (2019). Dose-Finding Designs for Early-Phase Cancer Clinical Trials, Springer, ISBN 978-4-431-55585-8.
• Dörre, A., Emura, T. (2019). Analysis of Doubly Truncated Data, Springer, ISBN 978-981-13-6241-5.
• Emura, T., Matsui, S., Rondeau, V. (2019). Survival Analysis with Correlated Endpoints, Springer, ISBN 978-981-13-3516-7.
• Funatogawa, I., Funatogawa, T. (2018). Longitudinal Data Analysis, Springer, ISBN 978-981-10-0077-5.
• Liu, Y., Akashi, F., Taniguchi, M. (2018). Empirical Likelihood and Quantile Methods for Time Series, Springer, ISBN 978-981-10-0152-9.
• Mano, S. (2018). Partitions, Hypergeometric Systems, and Dirichlet Processes in Statistics, Springer, ISBN 978-4-431-55888-0.
• Kunitomo, N., Sato, S., Kurisu, D. (2018). Separating Information Maximum Likelihood Method for High-Frequency Financial Data, Springer, ISBN 978-4-431-55930-6.
• Hirukawa, M. (2018). Asymmetric Kernel Smoothing, Springer, ISBN 978-981-10-5466-2.
• Emura, T., Chen, Y.-H. (2018). Analysis of Survival Data with Dependent Censoring, Springer, ISBN 978-981-10-7164-5.
• Hirakawa, Akihiro, Sato, Hiroyuki, Daimon, Takashi, Matsui, Shigeyuki (2018). Modern Dose-Finding Designs for Cancer Phase I Trials: Drug Combinations and Molecularly Targeted Agents, Springer, ISBN: 978-4-431-55573-5.
• Hosoya, Yuzo, Oya, Kosuke, Takimoto, Taro, Kinoshita, Ryo (2017). Characterizing Interdependencies of Multiple Time Series, Springer, ISBN: 978-981-10-6436-4.
• Akahira, Masafumi (2017). Statistical Estimation for Truncated Exponential Families, Springer, ISBN: 978-981-10-5296-5.
• Mori, Yuichi, Kuroda, Masahiro, Makino, Naomichi (2016). Nonlinear Principal Component Analysis and Its Applications, Springer, ISBN: 978-981-10-0159-8.
• Hamasaki, T., Asakura, K., Evans, S.R., Ochiai, T. (2016). Group-Sequential Clinical Trials with Multiple Co-Objectives, Springer, ISBN: 978-4-431-55900-9. 
• Sakata, Toshio, Sumi, Toshio, Miyazaki, Mitsuhiro (2016). Algebraic and Computational Aspects of Real Tensor Ranks, Springer, ISBN: 978-4-431-55459-2.
• Sakata, Toshio (Ed.) (2016). Applied Matrix and Tensor Variate Data Analysis, Springer, ISBN: 978-4-431-55387-8.
• Peters, Gareth W, Matsui, Tomoko (Eds.) (2015). Modern Methodology and Applications in Spatial-Temporal Modeling, Springer, ISBN: 978-4-431-55339-7.
• Tanokura, Yoko, Kitagawa, Genshiro (2015). Indexation and Causation of Financial Markets, Springer, ISBN: 978-4-431-55276-5.
• Peters, Gareth William, Matsui, Tomoko (Eds.) (2015). Theoretical Aspects of Spatial-Temporal Modeling, Springer, ISBN: 978-4-431-55336-6. 
• Ohtsu, Kohei, Peng, Hui, Kitagawa, Genshiro (2015). Time Series Modeling for Analysis and Control: Advanced Autopilot and Monitoring Systems, Springer, ISBN: 978-4-431-55302-1.