Publications

Book chapters:

T. Sei (2021).
Regression analysis for imbalanced binary data: Multi-dimensional Case,
in ``Pioneering Works on Extreme Value Theory -- In Honor of Masaaki Sibuya'', (Editors: N. Hoshino, S. Mano, T. Shimura), Springer, pp. 55--70.
(doi:10.1007/978-981-16-0768-4)
[publisher's site]

Kashimura, T., Sei, T., Takemura, A. and Tanaka, K. (2012).
Cones of elementary imsets and supermodular functions: a review and some new results,
in Harmony of Groebner Bases and the Modern Industrial Society, (Editor: T. Hibi), World Scientific, pp.117--152.
(doi:10.1142/9789814383462_0008)
[publisher's site] [preprint]

Published papers:

[32] 
Sukeda, I. and Sei, T. (2024).
Frank copula is minimum information copula under fixed Kendall’s tau,
Statistics and Probability Letters, 217, 110289.
[https://doi.org/10.1016/j.spl.2024.110289]

[31] 
Sei, T. and Komaki, F. (2024).
A harmonic property of right invariant priors.
Information Geometry, 2024, accepted.
[https://doi.org/10.1007/s41884-024-00133-4]

[30] 
Takazawa, Y. and Sei, T. (2024).
Maximum likelihood estimation of log-concave densities on tree space.
Statistics and Computing, 34, 84.
[https://doi.org/10.1007/s11222-024-10400-0]

[29] 
Chen, Y. and Sei, T. (2024).
A proper scoring rule for minimum information bivariate copulas,
Journal of Multivariate Analysis, 201, 105271.
[https://doi.org/10.1016/j.jmva.2023.105271]

[28]
Sei, T. and Yano, K. (2024).
Minimum information dependence modelling,
Bernoulli, 30 (4), 2623-2643.
[https://doi.org/10.3150/23-BEJ1687]

[27] 
Yoshimitsu, N., Maeda, T. and Sei, T. (2023).
Estimation of source parameters using a non-Gaussian probability density function in a Bayesian framework,
Earth, Planets and Space, 75, 33.
[https://doi.org/10.1186/s40623-023-01770-2]

[26] 
Sei, T. (2024).
Conditional inference of Poisson models and information geometry: an ancillary review,
Information Geometry, 7, 131–150.
[https://doi.org/10.1007/s41884-022-00082-w]

[25] 
Sei, T. (2022).
A quantile general index derived from the maximum entropy principle,
Entropy, 24, 1431.
[https://www.mdpi.com/1099-4300/24/10/1431]

[24] 
Sei, T. and Komaki, F. (2022).
A correlation-shrinkage prior for Bayesian prediction of the two-dimensional Wishart model,
Biometrika, 109 (4), 1173--1180.
[https://doi.org/10.1093/biomet/asac006]

[23] 
Bando, T., Sei, T. and Yata, K. (2022).
Consistency of the objective general index in high-dimensional setting,
Journal of Multivariate Analysis, 189, 104938.
[https://doi.org/10.1016/j.jmva.2021.104938]

[22] 
Sei, T. (2022).
Coordinate-wise transformation of probability distributions to achieve a Stein-type identity,
Information Geometry, 5, 325--354.
[https://doi.org/10.1007/s41884-021-00051-9]

[21] 
Ogawa, M., Nakamoto, K. and Sei, T. (2020).
On the fractional moments of a truncated centered multivariate normal distribution,
Communications in Statistics -- Simulation and Computation, 51 (7), 3923--3942.
[https://doi.org/10.1080/03610918.2020.1725821]

[20] 
Härkönen, M., Sei, T. and Hirose, Y. (2020).
Holonomic extended least angle regression,
Information Geometry, 3 (2), 149-181.
(doi:10.1007/s41884-020-00035-1)
[journal]

[19] 
Charles, V. and Sei, T. (2019).
A two-stage OGI approach to compute the regional competitiveness index,
Competitiveness Review, 29 (2), 78--95.
 (doi:10.1108/CR-08-2017-0050)

[18] 
Kume, A. and Sei, T. (2018).
On the exact maximum likelihood inference of Fisher-Bingham distributions using an adjusted holonomic gradient method,
Statistics and Computing, 28 (4), 835--847.
 (doi:10.1007/s11222-017-9765-3)
[journal]

[17] 
Sei, T. (2016).
An objective general index for multivariate ordered data,
Journal of Multivariate Analysis, 147, 247--264.
 (doi:10.1016/j.jmva.2016.02.005)
[journal] [preprint]

[16] 
Tanaka, K., Studený, M., Takemura, A., and Sei, T. (2015).
A linear-algebraic tool for conditional independence inference,
Journal of Algebraic Statistics, 6 (2), 150--167.
 (doi:10.18409/jas.v6i2.46)
[journal]

[15] 
Sei, T. and Kume, A. (2015).
Calculating the normalising constant of the Bingham distribution on the sphere using the holonomic gradient method,
Statistics and Computing, 25 (2), 321--332.
 (doi:10.1007/s11222-013-9434-0)
[journal] [preprint] [errata]

[14] 
Sei, T. (2014).
Infinitely imbalanced binomial regression and deformed exponential families,
Journal of Statistical Planning and Inference, 149, 116--124.
 (doi:10.1016/j.jspi.2014.01.002)
[journal] [preprint]

[13] 
Sei, T. (2013).
A Jacobian inequality for gradient maps on the sphere and its application to directional statistics,
Communications in Statistics - Theory and Methods, 42 (14), 2525--2542.
 (doi:10.1080/03610926.2011.563017)
[journal] [preprint]

[12] 
Sei, T., Shibata, H., Takemura, A., Ohara, K. and Takayama, N. (2013).
Properties and applications of Fisher distribution on the rotation group,
Journal of Multivariate Analysis, 116, 440--455.
 (doi:10.1016/j.jmva.2013.01.010)
[journal] [preprint]

[11] 
Rueschendorf, L. and Sei, T. (2012).
On optimal stationary couplings between stationary processes,
Electronic Journal of Probability, 17 (17), 1--20.
 (doi:10.1214/EJP.v17-1797)
[journal] [preprint]

[10] 
Hara, H., Sei, T. and Takemura, A. (2012).
Hierarchical subspace models for contingency tables,
Journal of Multivariate Analysis, 103 (1), 19--34.
 (doi:10.1016/j.jmva.2011.06.003)
[journal] [preprint]

[9] 
Nakayama H., Nishiyama K., Noro M., Ohara K., Sei, T., Takayama, N. and Takemura A. (2011).
Holonomic gradient descent and its application to the Fisher–Bingham integral,
Advances in Applied Mathematics, 47 (3), 639--658.
 (doi:10.1016/j.aam.2011.03.001)
[journal] [preprint]

[8] 
Sei, T. (2011).
Gradient modeling for multivariate quantitative data,
Annals of the Institute of Statistical Mathematics, 63 (4), 675-688.
 (doi:10.1007/s10463-009-0261-1)
[journal] [preprint]

[7] 
Kashimura, T., Sei, T., Takemura, A. and Tanaka, K. (2011)
Properties of semi-elementary imsets as sums of elementary imsets,
Journal of Algebraic Statistics, 2 (1), 14--35.
 (doi:10.18409/jas.v2i1.8)
[journal] [preprint]

[6] 
Sei, T. (2011).
A structural model on a hypercube represented by optimal transport,
Statistica Sinica, 21 (3), 1291-1314.
 (doi:10.5705/ss.2009.022)
[journal] [preprint]

[5] 
Sei, T. (2011).
Efron's curvature of the structural gradient model,
Journal of the Japan Statistical Society, 41 (1), 51--66.
[journal paper] [preprint]

[4] 
Sei, T., Aoki, S. and Takemura, A. (2009).
Perturbation method for determining the group of invariance of hierarchical models,
Advances in Applied Mathematics, 43 (4), 375--389.
 (doi:10.1016/j.aam.2009.02.005)
[journal] [preprint]

[3] 
Sei, T. and Komaki, F. (2008).
Information geometry of small diffusions,
Statistical Inference for Stochastic Processes, 11 (2), 123--141.
 (doi:10.1007/s11203-007-9011-2)
[journal]

[2] 
Sei, T. and Komaki, F. (2007).
Bayesian prediction and model selection for locally asymptotically mixed normal models,
Journal of Statistical Planning and Inference, 137 (7), pp. 2523--2534.
 (doi:10.1016/j.jspi.2006.10.002)
[journal] [preprint]

[1] 
Sei, T. (2007).
Local asymptotic mixed normality of transformed Gaussian models for random fields,
Stochastic Processes and their Applications, 117 (3), pp. 375--398.
 (doi:10.1016/j.spa.2006.08.007)
[journal]

Ph. D. thesis:

Sei, T. (2005). Asymptotic properties of estimators and information criteria for random fields,
Ph. D. thesis, Graduate School of Information Science and Technology, the University of Tokyo, Japan.
phd-sei.pdf

Preprints:

Sei, T. (2024).
Constructing Markov chains with given dependence and marginal stationary distributions,
Preprint, arXiv:2407.17682.
https://arxiv.org/abs/2407.17682

Sukeda, I. and Sei, T. (2024).
Frank copula is minimum information copula under fixed Kendall's $\tau$,
Preprint, arXiv:2406.14814.
https://arxiv.org/abs/2406.14814

Sukeda, I. and Sei, T. (2023).
On the minimum information checkerboard copulas under fixed Kendall's rank correlation,
Preprint, arXiv:2306.01604.
https://arxiv.org/abs/2306.01604

Takazawa, Y. and Sei, T. (2022).
Maximum likelihood estimation of log-concave densities on tree space,
Preprint, arXiv:2211.12037.
https://arxiv.org/abs/2211.12037

Sei, T. and Yano, K. (2022).
Minimum information dependence modeling,
Preprint, arXiv:2206.06792.
https://arxiv.org/abs/2206.06792

Chen, Y. and Sei, T. (2022).
A proper scoring rule for minimum information copulas,
Preprint, arXiv:2204.03118.
http://arxiv.org/abs/2204.03118

Yanagi, M. and Sei, T. (2022).
Improving randomization tests under interference based on power analysis,
Preprint, arXiv:2203.10469.
https://arxiv.org/abs/2203.10469

Sei, T. and Matsumoto, K. (2019).
Properties of divergence for semiparametric copula models,
Technical Report METR2019-11, Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo.
https://www.keisu.t.u-tokyo.ac.jp/data/2019/METR19-11.pdf

Sei, T. (2018).
Inconsistency of diagonal scaling under high-dimensional limit: a replica approach,
Preprint, arXiv:1808.05781.
https://arxiv.org/abs/1808.05781

Sei, T. (2017).
Coordinate-wise transformation of probability distributions to achieve a Stein-type identity,
Technical Report METR2017-04, Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo.
https://www.keisu.t.u-tokyo.ac.jp/data/2017/METR17-04.pdf

Sei, T. (2006).
Parametric modeling based on the gradient maps of convex functions,
Technical Report METR2006-51, Department of Mathematical Informatics, Graduate School of Information Science and Technology, The University of Tokyo.
https://www.keisu.t.u-tokyo.ac.jp/data/2006/METR06-51.pdf
[Published in Annals of the Institute of Statistical Mathematics
with title changed to Gradient modeling for multivariate quantitative data.]