All papers

  1. Y. Komori and K. Burrage (2023), Split S-ROCK methods for high-dimensional stochastic differential equations, Journal of Scientific Computing, 97 (3), 62.
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  2. Y. Komori, G. Yang and K. Burrage (2023), Formulae for mixed moments of Wiener processes and a stochastic area integral, SIAM Journal on Numerical Analysis, 61 (4), 1716-1736.
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  3. G. Yang, K. Burrage, Y. Komori and X. Ding (2022), A new class of structure-preserving stochastic exponential Runge-Kutta integrators for stochastic differential equations, BIT Numerical Mathematics, 62 (4), 1591-1623.
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  4. A. Tocino, Y. Komori and T. Mitsui (2022), Integration of the stochastic underdamped harmonic oscillator by the theta-method, Mathematics and Computers in Simulation, 199, 217-230.
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  5. G. Yang, K. Burrage, Y. Komori, P. Burrage and X. Ding (2021), A class of new Magnus-type methods for semi-linear non-commutative Ito stochastic differential equations, Numerical Algorithms, 88, 1641-1665.
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  6. Y. Komori, A. Eremin and K. Burrage (2019), S-ROCK methods for stochastic delay differential equations with one fixed delay, Journal of Computational and Applied Mathematics, 353, 345-354.
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  7. Y. Komori, D. Cohen and K. Burrage (2017), Weak second order explicit exponential Runge-Kutta methods for stochastic differential equations, SIAM Journal on Scientific Computing, 39 (6), A2857-A2878.
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  8. Y. Komori (2015), Suitable algorithm associated with a parameterization for the three-parameter lognormal distribution, Communications in Statistics - Simulation and Computation, 44 (1), 239-246 (letter).
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  9. Y. Komori and K. Burrage (2014), A stochastic exponential Euler scheme for simulation of stiff biochemical reaction systems, BIT Numerical Mathematics, 54 (4), 1067-1085.
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  10. Y. Komori and E. Buckwar (2013), Stochastic Runge-Kutta methods with deterministic high order for ordinary differential equations, BIT Numerical Mathematics, 53 (3), 617-639.
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  11. Y. Komori and K. Burrage (2013), Strong first order S-ROCK methods for stochastic differential equations, Journal of Computational and Applied Mathematics, 242, 261-274.
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  12. Y. Komori and K. Burrage (2012), Weak second order S-ROCK methods for Stratonovich stochastic differential equations, Journal of Computational and Applied Mathematics, 236 (11), 2895-2908.
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  13. Y. Komori and K. Burrage (2011), Supplement: efficient weak second order stochastic Runge-Kutta methods for non-commutative Stratonovich stochastic differential equations, Journal of Computational and Applied Mathematics, 235 (17), 5326-5329 (letter).
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  14. Y. Komori (2008), Statistical analysis related to impulse tests for self-restoring insulation, IEEJ Transactions on Electrical and Electronic Engineering, 3 (6), 680-687.
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  15. Y. Komori (2008), Weak first- or second-order implicit Runge-Kutta methods for stochastic differential equations with a scalar Wiener process, Journal of Computational and Applied Mathematics, 217 (1), 166-179.
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  16. Y. Komori (2007), Weak second-order stochastic Runge-Kutta methods for non-commutative stochastic differential equations, Journal of Computational and Applied Mathematics, 206 (1), 158-173.
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  17. Y. Komori (2007), Weak order stochastic Runge-Kutta methods for commutative stochastic differential equations, Journal of Computational and Applied Mathematics, 203 (1), 57-79.
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  18. Y. Komori (2007), Multi-colored rooted tree analysis of the weak order conditions of a stochastic Runge-Kutta family, Applied Numerical Mathematics, 57 (2), 147-165.
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  19. Y. Komori (2006), Properties of the Weibull cumulative exposure model, Journal of Applied Statistics, 33 (1), 17-34.
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  20. Y. Komori and H. Hirose (2004), Easy estimation by a new parameterization for the three-parameter lognormal distribution, Journal of Statistical Computation and Simulation, 74 (1), 63-74.
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  21. H. Hirose and Y. Komori (2003), Maximum likelihood estimation in a mixture regression model using the continuation method, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, E86-A (5), 1256-1265.
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  22. H. Hirose and Y. Komori (2002), A consideration on the maximum likelihood estimation in a mixture regression model using the EM algorithm, Far East Journal of Theoretical Statistics, 7 (2), 111-127.
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  23. Y. Komori and H. Hirose (2002), Parameter estimation based on grouped or continuous data for truncated exponential distributions, Communications in Statistics: Theory and Methods, 31 (6), 889-900.
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  24. Y. Komori and H. Hirose (2000), An easy parameter estimation by the EM algorithm in the new up-and-down method, IEEE Transactions on Dielectrics and Electrical Insulation, 7 (6), 838-842.
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  25. Y. Komori and H. Hirose (2000), Bias in the estimator of the new up-and-down method, INFORMATION, 3 (2), 183-192 (in Japanese).

  26. H. Hirose and Y. Komori (1999), A remark on the new up-and-down method analysis, IEEJ Transactions on Fundamentals and Materials, 119 (4), 527-528 (letter in Japanese).

  27. Y. Komori, T. Mitsui, and H. Sugiura (1997), Rooted tree analysis of the order conditions of ROW-type scheme for stochastic differential equations, BIT, 37 (1), 43-66.
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  28. Y. Komori and T. Mitsui (1995), Stable ROW-type weak scheme for stochastic differential equations, Monte Carlo Methods and Applications, 1 (4), 279-300.
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  29. Y. Komori, Y. Saito and T. Mitsui (1994), Some issues in discrete approximate solution for stochastic differential equations, Computers & Mathematics with Applications, 28 (10-12), 269-278.
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Last updated: 2023/10/31