Papers

2022

• Muni Toke, I., Yoshida, N.: Marked point processes and intensity ratios for limit order book modeling. arXiv:2001.08442 (2020). Japanese Journal of Statistics and Data Science (2022)

2021

• Fang, X. and Koike, Y. High-dimensional central limit theorems by Stein's method. Annals of Applied Probability, Volume 31, Issue 4, 1660-1686 (2021).
• Gloter, A., Yoshida, N.: Adaptive estimation for degenerate diffusion processes. Electronic Journal of Statistics, 15(1), 1424-1472 (2021)
• Inatsugu, H., Yoshida, N.:  Global jump filters and quasi likelihood analysis for volatility. arXiv:1806.10706 (2018) Annals of the Institute of Statistical Mathematics volume 73, pages 555–598 (2021) Electronic supplementary material (2021), updated by arXiv:1806.10706v3
• Kaino, Y. and Uchida, M. Parametric estimation for a parabolic linear SPDE model based on discrete observations. Journal of Statistical Planning and Inference, Volume 211, 190-220. (2021).
• Kaino, Y. and Uchida, M.  Adaptive estimator for a parabolic linear SPDE with a small noise. Japanese Journal of Statistics and Data Science volume 4, pages 513–541 (2021)
• Koike, Y. Notes on the dimension dependence in high-dimensional central limit theorems for hyperrectangles. Japanese Journal of Statistics and Data Science, Volume 4, Issue 1, 257-297 (2021).
• Koike, Y.: Inference for time-varying lead-lag relationships from ultra high frequency data. Japanese Journal of Statistics and Data Science, Volume 4, Issue 1, 643-696 (2021).
• Nakakita, S. H., Kaino, Y. and Uchida, M. Quasi-likelihood analysis and Bayes-type estimators of an ergodic diffusion plus noise. Annals of the Institute of Statistical Mathematics, Volume 73, Issue 1, 177-225. (2021).

2020

• Bierkens, J., Grazzi, S., Kamatani, K. and Roberts, G. O. Boomerang Sampler ICML 2020. arXiv:2006.13777 (2020)
• Kaino, Y., Nakakita, S. H. and Uchida, M. Hybrid estimation for ergodic diffusion processes based on noisy discrete observations. Statistical Inference for Stochastic Processes, Volume 23, Issue 1, 171-198. (2020).
• Kamatani, K. Random walk Metropolis algorithm in high dimension with non-Gaussian target distributions. Stochastic processes and their applications, Volume 130, Issue 1, January 2020, Pages 297-327
• Koike, Y.: De-biased graphical Lasso for high-frequency data. Entropy, 22 (2020), no.4, 456.
• Nakakita, S. H. and Uchida, M. Parametric estimation for convolutionally observed diffusion processes. Special Issue "Machine Learning Meets Stochastic Processes: New Trends for Understanding Complex Systems". Entropy, Volume 22, Issue 9, 1031. (2020).
• Podolskij, M., Veliyev, B., Yoshida, N.: Edgeworth expansion for Euler approximation of continuous diffusion processes. arXiv:1811.07832v1  (2018),  Annals of Applied Probability, Vol. 30, No. 4, 1971-2003 (2020)
• Suzuki, T., Yoshida, N.: Penalized least squares approximation methods and their applications to stochastic processes. arXiv:1811.09016 (2018), Japanese Journal of Statistics and Data Science, on-line (2020)
• Tudor, C., Yoshida, N.: Asymptotic expansion of the quadratic variation of a mixed fractional Brownian motion. Statistical Inference for Stochastic Processes (2020)

2019

• Nualart, D., Yoshida, N.: Asymptotic expansion of Skorohod integrals. arXiv:1801.00120 (2017) Electronic Journal of Probability Volume 24 (2019), paper no. 119, 64 pp
• Muni Toke, I., Yoshida, N.:  Analyzing order flows in limit order books with ratios of Cox-type intensities. arXiv:1805.06682 (2018) Quantitative Finance online: 21 Aug 2019.
• Bishop, A. N., Del Moral, P., Kamatani, K., and Remillard, B. On one-dimensional Riccati diffusions. arXiv:1711.10065, Ann. Appl. Probab. Volume 29, Number 2 (2019), 1127-1187.
• Eguchi, Shoichi and Masuda, H.: Data driven time scale in Gaussian quasi-likelihood inference. arXiv:1801.10378, October 2019, Volume 22, Issue 3, pp 383–430
• Hayashi, T. and Koike, Y.: No arbitrage and lead-lag relationships. Statistics and Probability Letters, 154 (2019), 108530.
• Jasra, A and Kamatani, K. and Masuda, H.: Bayesian inference for stable Lévy driven stochastic differential equations with high-frequency data. arXiv:1707.08788, Scandinavian Journal of statistics, Volume46, Issue2, June 2019, Pages 545-574
• Koike, Y.: Gaussian approximation of maxima of Wiener functionals and its application to high-frequency data. Annals of Statistics, 47 (2019), no.3, pp 1663-1687.
• Koike, Y.: Mixed-normal limit theorems for multiple Skorohod integrals in high-dimensions, with application to realized covariance. Electronic Journal of Statistics, 13 (2019), no.1, pp 1443-1522.
• Koike, Y. and Liu, Z.: Asymptotic properties of the realized skewness and related statistics. Annals of the Institute of Statistical Mathematics, 71 (2019), no. 4, pp 703-741.
• Koike, Y. and Tanoue, Y.: Oracle inequalities for sign constrained generalized linear models. Econometrics and Statistics, 11 (2019), pp 145-157.
• Masuda, H. Non-Gaussian quasi-likelihood estimation of locally stable SDE. arXiv:1608.06758, Stochastic Processes and their Applications, Volume 129, Issue 3, March 2019, Pages 1013-1059
• Nakakita, S. H. and Uchida, M.: Inference for ergodic diffusions plus noise. arXiv:1805.11414.Scandinavian Journal of Statistics, Volume46, Issue2, June 2019, Pages 470-516
• Nakakita, S. H. and Uchida, M.; Adaptive test for ergodic diffusions plus noise. arXiv:1804.01864. , Journal of Statistical Planning and Inference, Volume 203, December 2019, Pages 131-150
• Tudor, C., Yoshida, N.: Asymptotic expansion for vector-valued sequences of random variables with focus on Wiener chaos. arXiv:1712.03123, Stochastic Processes and their Applications, Volume 129, Issue 9, September 2019, Pages 3499-3526
• Uehara, Y: Statistical inference for misspecified ergodic Lévy driven stochastic differential equation models. arXiv:1702.00908. Volume 129, Issue 10, October 2019, Pages 4051-4081
• Umezu, Y., Shimizu, Yusuke, Masuda, H. and Ninomiya, Y.: AIC for Non-concave Penalized Likelihood Method. arXiv:1509.01688v2. Annals of the Institute of Statistical Mathematics, April 2019, Volume 71, Issue 2, pp 247–274.

2018

• Brouste, A. and Masuda, H.: Efficient estimation of stable Lévy process with symmetric jumps.Statistical Inference for Stochastic Processes July 2018, Volume 21, Issue 2, pp 289–307.
• Eguchi, Shoichi: Model comparison for dependent generalized linear model. arXiv:1601.01082v1.  Econometrics and Statistics 5 (2018), pp171-188, https://doi.org/10.1016/j.ecosta.2017.04.003
• Eguchi, Shoichi and Masuda, H.: Schwarz type model comparison for LAQ models.  arXiv:1606.01627, Bernoulli 24.3 (2018), pp 2278-2327
• Hayashi, T. and Koike, Y.: Wavelet-based methods for high-frequency lead-lag analysis. SIAM Journal on Financial Mathematics, 9 (2018), no.4, pp 1208-1248.
• Hirose, K. and Masuda, H.: Robust relative error estimation. Entropy, 20(9), 632 (2018, Aug). [doi:10.3390/e20090632]
• Iacus, S., Yoshida, N.: Simulation and Inference for Stochastic Processes with YUIMA: A Comprehensive R Framework for SDEs and Other Stochastic Processes. Springer (2018)
• Jasra, A., Kamatani, K, Osei, P., Zhou, Y: Multilevel Particle Filters: Normalizing Constant Estimation. Statistics and Computing 28.1, pp47-60, DOI https://doi.org/10.1007/s11222-016-9715-5
• Jasra, A., Kamatani, K, Kody, L., Zhou, Y: A MULTI-INDEX MARKOV CHAIN MONTE CARLO METHOD. International Journal for Uncertainty Quantification 8.1, pp61-73, DOI 10.1615/Int.J.UncertaintyQuantification.2018021551
• Kaino, Y. and Uchida, M.: Hybrid estimators for stochastic differential equations from reduced data. Statistical Inference for Stochastic Processes, Volume 21, Issue 2, pp 435–454 (2018), http://doi.org/10.1007/s11203-018-9184-x
• Kaino, Y. and Uchida, M.: Hybrid estimators for diffusion processes with small noises from reduced data. Metrika, 81(7), 745-773, (2018), http://doi.org/10.1007/s00184-018-0657-0
• Kamatani, K.: Efficient strategy of Markov chain Monte Carlo method for high-dimensional heavy-tail distribution. Bernoulli, Volume 24, Number 4B (2018), 3711-3750. doi:10.3150/17-BEJ976
• Shimizu, Yusuke: Asymptotic behavior of regularized estimator under multiple and mixed-rates asymptotics. Josai Mathematical Monographs, 11pp.3 - 14 , 2018-3
• Yoshida, N.: Partial quasi likelihood analysis. arXiv:1801.00279 Jpn J Stat Data Sci (2018) 1:157–189

2017

• Beskos, A., Crisan, D., Jasra, A., Kamatani, K, Zhou, Y: A stable particle filter in high-dimensions. arXiv:1412.3501. Advances in Applied Probability 49.1. (2017), DOI https://doi.org/10.1017/apr.2016.77
• Clinet, S., Yoshida, N.: Statistical Inference for Ergodic Point Processes and Limit Order Book. arXiv:1512.01899, Stochastic Processes and their Applications, Volume 127, Issue 6, (2017), Pages 1800-1839
• Jasra, A., Kamatani, K, Law, J. H., Zhou, Y: Multilevel particle filters. SIAM: SIAM Journal on Numerical Analysis 55 (6), pp 3068-3096
• Kaino, Y., Uchida, M. and Yoshida, Y.: Hybrid estimation for an ergodic diffusion process based on reduced data. Bulletin of Informatics and Cybernetics, 49, 89-118 (2017).
• Kamatani, K: Ergodicity of Markov chain Monte Carlo with reversible proposal. arXiv:1602.02889. Journal of Applied Probability 54.2. (2017), DOI https://doi.org/10.1017/jpr.2017.22
• Koike, Y.: Time endogeneity and an optimal weight function in pre-averaging covariance estimation. Statistical Inference for Stochastic Processes 20 (1), pp 15–56
• Koike, Y.: On the asymptotic structure of Brownian motions with a small lead-lag effect. Journal of the Japan Statistical Society 47 (2), pp 1-31.
• Masuda, H., Uehara, Y.: Two-step estimation of ergodic Lévy driven SDE. Statistical Inference for Stochastic Processes, Volume 20, Issue 1 (2017), pp 105–137
• Muni Toke, I., Yoshida, N.: Modelling intensities of order flows in a limit order book. arXiv:1602.03944, Quantitative Finance, Volume 17, (2017) - Issue 5, 683-701
• Masuda, H., Shimizu, Yusuke: Moment convergence in regularized estimation under multiple and mixed-rates asymptotics. arXiv:1406.6751v3, Mathematical Methods of Statistics, 26 (2017), no.2, pp 81--110. [doi: 10.3103/S1066530717020016]
• Podolskij, M., Veliyev, B., Yoshida, N.: Edgeworth expansion for the pre-averaging estimator. arXiv:1512.04716 (2015). Stochastic Processes and their Applications 127 (11), pp 3558-3595
• Shimizu, Yasutaka: Threshold estimation for stochastic processes with small noise. arXiv:1502.07409v2, Scandinavian Journal of Statistics vol. 44, issue 4, 951-988
• Shimizu, Yusuke: Moment convergence of regularized least-squares estimator for linear regression model. Annals of the Institute of Statistical Mathematics, 2017, Volume 69, Issue 5, pp 1141–1154
• 内田雅之: 高頻度データに基づく確率微分方程式モデルのハイブリッド推定, 統計数理, 第65巻, 第1号, 39-69, (2017).
• 上原悠槙, 増田弘毅: Lévy駆動型確率微分方程式の段階的推定について, 統計数理, 第65巻第1号21--38.

2016

• Kamatani, K., Nogita, A. and Uchida, M. Hybrid multi-step estimation of the volatility for stochastic regression models. Bulletin of Informatics and Cybernetics, Volume 48, (2016), 19-35 (2016)
• Kimura, A., Yoshida, N.: Estimation of correlation between latent processes, Advanced Modelling in Mathematical Finance pp 131-146, 2016
• Nomura, R. and Uchida, M. Adaptive Bayes estimators and hybrid estimators for small diffusion processes based on sampled data, Journal of the Japan Statistical Society, Vol. 46 (2016) No. 2 p. 129-154, http://doi.org/10.14490/jjss.46.129
• Podolskij, M., Yoshida. N.: Edgeworth expansion for functionals of continuous diffusion processes, The Annals of Applied Probability, Volume 26, Number 6 (2016), 3415-3455.
• Uchida, M., Yoshida, N.: Model selection for volatility prediction. In: The Fascination of Probability, Statistics and their Applications. In Honour of Ole E. Barndorff-Nielsen, Editors: Mark Podolskij, Robert Stelzer, Steen Thorbjørnsen, Almut E. D. Veraart, 343-360, Springer 2016, https://doi.org/10.1007/978-3-319-25826-3_16

2015

• Hino, H., Koshijima, K., Murata, N.: Non-parametric entropy estimators based on simple linear regression. Computational Statistics and Data Analysis, Volume 89, 2015, Pages 72-84
• Ivanenko, D., Kulik, A. M., Masuda, H.: Uniform LAN property of locally stable Lévy process observed at high frequency. ALEA - Latin American Journal of Probability and Mathematical Statistics 12 (2015), 835--862.
• 増田 弘毅: 非正規ノイズ型エルゴード過程の推定. 日本統計学会誌和文誌, 44(2), 471-495 (2015)
• Masuda, H. Parametric estimation of Lévy processes. Lévy Matters IV, Estimation for Discretely Observed Lévy Processes, Lecture Notes in Mathematics, vol. 2128, 179-286 (2015)

2014

• Feng, R., Shimizu, Y.: Potential measures for spectrally negative Markov additive processes with applications in ruin theory. Insurance: Mathematics and Economics, vol.59, 11-26 (2014)

To appear

• Yoshida, N.: Quasi-likelihood analysis and its applications. Statistical Inference for Stochastic Processes (2022)
• Mishura, Y., Yoshida, N.: Divergence of an integral of a process with small ball estimate. arXiv:2102.01616 (2021), Stochastic Processes and their Applications
• Delattre, S., Gloter, A.,  Yoshida, N.: Rate of Estimation for the Stationary Distribution of Stochastic Damping Hamiltonian Systems with Continuous Observations. arXiv:2001.10423 (2020), Annales de l'Institut Henri Poincaré
• Beskos, A. and Kamatani, K. MCMC Algorithms for Posteriors on Matrix Spaces, 2020. arXiv:2008.02906 (2020)
• Bierkens, J., Kamatani, K. and Roberts G. O.: High-dimensional scaling limits of piecewise deterministic sampling algorithms. arXiv:1807.11358

Preprint

• Inatsugu, H., Yoshida, N.:  Global jump filters and realized volatility. arXiv:2102.05307v2  (2021)
• Yoshida, N.: Simplified quasi-likelihood analysis for a locally asymptotically  quadratic random field. aXiv:2102.12460 (2021)
• Yoshida, N.: Asymptotic expansion of a variation with anticipative weights. arXiv:2101.00089 (2020)
• Kamatani, K. and Song, X. Non-reversible guided Metropolis-Hastings kernel. 2020. arXiv:2005.05584 (2020)
• Gloter, A., Yoshida, N.: Adaptive and non-adaptive estimation for degenerate diffusion processes. arXiv:2002.10164 (2020)
• Kinoshita, Y., Yoshida, N.: Penalized quasi likelihood estimation for variable selection. arXiv:1910.12871 (2019)
• Ogihara, T, Yoshida, N.: Quasi likelihood analysis of point processes for ultra high frequency data. arXiv:1512.01619 (2015)
• Shimizu, Yusuke: Update estimation of diffusion parameter observed at high frequency. arXiv:1506.08521v1