Research

Unpublished Manuscripts (Working paper etc.)

  1. Matsui, M., Mikosch, T., Roozegar, R. and Tafakori, L. (2021) Distance covariance for random fields, arXiv:2107.03162. (to appear in Stochastic Processes and their Applications)

  2. Damek, E. and Matsui, M. (2021) Tails of bivariate stochastic recurrence equation with triangular matrices. (to appear in Stochastic Processes and their Applications)

  3. Approximated likelihood estimation for stable laws/OU processes (joint with Sueishi, N.)

  4. Matsui, M. (2016) Log-convexity and the cycle index polynomials with relation to compound Poisson distributions, arXiv:1609.06875.

  5. Endo, K. and Matsui, M.(2008) Generalized fractional Ornstein-Uhlenbeck processes, arXiv:0807.2110.

Refereed Journal Publications

  1. Matsui, M. and Pedersen, R.S. (2021) Characterization of the tail behavior of a class of BEKK processes: A stochastic recurrence equation approach. Econometric Theory, Cambridge.

  2. Matsui, M. (2021) Asymptotics of maximum likelihood estimation for stable law with continuous parameterization, Communications in Statistics -Theory and Methods, 50, 3695-3712.Taylor & Francis.

  3. Matsui, M. and Świątkowski, W. (2020) Tail indices for AX+B Recursion with Triangular Matrices. Journal of Theoretical Probability. Springer.

  4. Dehling, H., Matsui, M., Mikosch, T., Samorodnitsky, G. and Tafakori, L. (2020) Distance covariance for discretized stochastic processes. Bernoulli 26, 2758 - 2789. Institute of Mathematical Statistics and the Bernoulli society.

  5. Damek, E., Matsui, M. and Świątkowski, W. (2019) Componentwise different tail solutions for bivariate stochastic recurrence equations-- with application to GARCH(1,1) processes. Colloquium Mathematicum, 155, 227-254. Institute of Mathematics, Polish Academy of Sciences.

  6. Davis, R.A., Matsui, M., Mikosch, T. and Wan, P. (2018) Applications of distance correlation to time series.
    Bernoulli, 24, 3087-3116. Institute of Mathematical Statistics and the Bernoulli society.

  7. Matsui, M., Mikosch, T. and Samorodnitsky, G. (2017) Distance covariance for stochastic processes.
    Probability and Mathematical Statistics, 37, 355-372.Wroclaw University of Science and Technology.

  8. Matsui, M. (2017) Prediction of components in random sums.
    Methodology and Computing in Applied Probability, 19, 573-587, Springer.

  9. Matsui, M. and Rolski, T. (2016) Prediction in a mixed Poisson cluster model.
    Stochastic models, 32, 460-480. Taylor & Francis.

  10. Matsui, M., Mikosch, T. (2016) The Extremogram and the cross-Extremogram for a bivariate GARCH(1,1) Process. Advances in Applied Probability, 48A, 217-233. Applied Probability Trust.

  11. Matsui, M. and Pawlas, Z. (2016) Fractional absolute moments of heavy tailed distributions.
    Brazilian journal of probability and statistics, 30, 272-298. Brazilian Statistical Association.

  12. Kluppelberg, C. and Matsui, M. (2015) Generalized fractional L\'evy processes with fractional Brownian motion limit and applications to stochastic volatility models.
    Advances in Applied Probability, 47, 1108-1131.     Applied Probability Trust.

  13. Matsui, M. and Yoshimi, T. (2015) Macroeconomic dynamics in a model with heterogeneous wage contracts.
    Economic Modelling, 49, 72-80. Elsevier.

  14. Matsui, M. (2015) Prediction in a Poisson cluster model with multiple cluster processes.
    Scandinavian Actuarial Journal, 2015, 1-30. Taylor & Francis.

  15. Matsui, M. (2014) Prediction in a non-homogeneous Poisson cluster model. Insurance: Mathematics and Economics, 55, 10-17. Elsevier..

  16. Matsui, M. and Shieh, N.-R. (2014) The Lamperti Transform of fractional Brownian motion and related self-similar Gaussian processes.
    Stochastic models, 30, 68-98. Taylor & Francis.

  17. Matsui, M. and Yoshimi, T. (2013) Heterogeneity in wage rigidity and monetary policy. Review of Integrative Business and Economics Research, 2,
    489-520. Society of Interdisciplinary Business Research..

  18. Matsui, M., Mikosch, T. and Tafakori, L. (2013) Estimation of the tail index for integer-valued sequences. Extremes, 16, 429-455. Springer.

  19. Matsui, M and Shieh, N.-R. (2013) On the Exponential Process associated with a CARMA-type Process.
    Stochastics, 85, 743-762. Taylor & Francis.

  20. Behme, A. Maejima, M. Matsui, M. and Sakuma, N. (2012) Distributions of exponential integrals of independent increment processes related to generalized gamma convolutions. Bernoulli, 18, 1172-1187. Institute of Mathematical Statistics and the Bernoulli society.

  21. Matsui, M. (2011) Multiple Equilibria in Lucas (1972) model.
    The Journal of Social Science, 63, 91-109. Institute of Social Science, University of Tokyo.(in Japanese)

  22. Maejima, M. Matsui, M. and Suzuki, M．(2010) Classes of infnitely divisible distributions on Rd related to the class of selfdecomposable distributions. Tokyo Journal of Mathematics, 33, 453-386. Publication Committee for the TJM.

  23. Matsui, M. and Mikosch, T. (2010) Prediction in a Poisson cluster model.
    Journal of Applied Probability, 47, 350-366. Applied Probability Trust.

  24. Matsui, M. and Shieh, N.-R. (2009) On the Exponentials of Fractional Ornstein-Uhlenbeck Processes.
    Electronic Journal of Probability, 14, 594-611. Institute of Mathematical Statistics and the Bernoulli society.

  25. Matsui, M. and Takemura, A. (2009) Integral representations of one dimensional projections for multivariate stable densities. Journal of Multivariate Analysis, 100, 334-344. Elsevier.

  26. Endo, K. and Matsui, M. (2008) The stationarity of multidimensional generalized Ornstein-Uhlenbeck processes.
    Statistics & Probability Letters, 78, 2265-2272. Elsevier.

  27. Matsui, M. and Takemura, A. (2008) Goodness-of-Fit Tests for Symmetric Stable Distributions -- Empirical Characteristic Function Approach. TEST, 17, 546-566. Springer.

  28. Matsui, M. and Takemura, A. (2006) Some improvements in numerical evaluation of symmetric stable density and its derivatives. Communications in Statistics - Theory and Methods, 35, 149-172. Taylor & Francis.

  29. Matsui, M. (2005) Fisher information matrix of general stable distributions close to the normal distribution.
    Mathematical Methods of Statistics, 14, 224-251. Allerton Press, Inc.

  30. Matsui, M. and Takemura, A. (2005) Empirical characteristic function approach to goodness-of- fit tests for the Cauchy distribution with parameters estimated by MLE or EISE. Annals of the Institute of Statistical Mathematics, 57, 183-199. Springer.