Talks

2023 (Apr 2023 - Mar 2024)

  • Yoshida, N.: Asymptotic expansion for batched bandits. IMS-Asia-Pacific Rim Meeting 2024, Melbourne, Australia, January 4-7, 2024.
  • Yoshida, N.: 17th International Conference Computational and Financial Econometrics (CFE 2023), HTW Berlin, University of Applied Sciences, Berlin, Germany, December 16-18, 2023.
  • Yoshida, N.: Malliavin calculus and precise distributional approximations. Workshop on Eco-Stat Asymptotics 2023 (WESA2023), University of Verona, Verona, September 11, 2023
  • Yoshida, N.: Quasi-likelihood analysis and estimation for a degenerate diffusion process. 6th International Conference on Econometrics and Statistics (EcoSta 2023), Waseda, Tokyo, August 1-3, 2023.
  • Yoshida, N.: Higher-order asymptotic distribution theory with the Malliavin calculus and its applications to statistics. 64th ISI World Statistics Congress, IPS 150 - Statistical Inference For Stochastic Ordinary And Partial Differential Equations, Ottawa, Canada, July 16-20, 2023.
  • Yoshida, N.: Some recent developments in asymptotic expansion. Mathematical Finance and Stochastics: A Conference in Honor of David Nualart, San Sebastian, Spain, May 29-31, 2023.
  • Uehara, Y: Quasi-likelihood analysis for Student-Levy regression. 6th International Conference on Econometrics and Statistics (EcoSta 2023), Waseda, Tokyo, August 1-3, 2023.
  • Masuda, H.: Locally stable regression (May 19, 2023; Colloquium, University of Tokyo)
  • Masuda, H.: Consistent model selection for locally stable trend-scale regression (June 6, 2023; EFFI Japan-French statistics seminar, online)
  • Masuda, H.: Expanding quasi-likelihood inference for Lévy driven models (July 20; 64th ISI Statistics Congress - Ottawa, Canada)
  • Masuda, H.: Non-Gaussian Ornstein-Uhlenbeck regression (July 28; The 4th International Conference on Science, Mathematics, Environment and Education (ICoSMEE), virtual)

2022 (Apr 2022 - Mar 2023)

  • Masuda, H.: Formulae for comparing ergodic SDE models (June 30, 2022; Dynstoch meeting 2022, Paris, online)
  • Masuda, H.:Continuous non-Gaussian mixed-effects modeling (September 5, 2022; Japanese Joint Statistical Meeting 2022, Seikei University, Japan)
  • Masuda, H.:BIC-type model selection for locally stable regression (September 16, 2022; MSJ Autumn Meeting 2022, Hokkaido University, Japan)
  • Masuda, H.:On noise inference for ergodic Lévy driven SDE (December 8, 2022; Workshop: Infinitely divisible processes and related topics, ISM, Online)
  • Masuda, H.:Quasi-likelihood inference for Student-Lévy regression (December 18, 2022; CMStatistics, King's College London)
  • Masuda, H.:Mixed-effects location-scale model based on generalized hyperbolic distribution (March 7, 2023; CREST workshop, ISM, hybrid)
  • Yoshida, N.: Batched bandits and conditional Edgeworth expansion. DYNSTOCH 2023 - Workshop on Statistical Methods for Dynamical Stochastic Models, Imperial College London, March 28
  • Yoshida, N.: Partial mixing and asymptotic expansion for batched bandits. CMStatistics 2022 (online). King's College London, UK, December 19, 2022.
  • Uchida, M: Estimation for linear parabolic SPDEs in two space dimensions based on high-frequency data. CMStatistics 2022 (online). King's College London, December 18, 2022.
  • Yoshida, N.: Adaptive and non-adaptive estimation for degenerate diffusion processesStatistics of Stochastic Processes in Discrete and Continuous Time (on-line). Kyiv, Ukraine, October 11, 2022
  • Masuda, H.: BIC-type model selection for locally stable regression (September 16, 2022; MSJ Autumn Meeting 2022, Hokkaido University, Japan)
  • Uchida, M: Parameter estimation for a linear parabolic SPDE in two space dimensions with a small noise from discrete observations. Statistics for Stochastic Processes: SDEs, SPDEs and concentration of measure (online). University of Luxembourg, September 7, 2022 
  • Masuda, H.: Continuous non-Gaussian mixed-effects modeling (September 5, 2022; Japanese Joint Statistical Meeting 2022, Seikei University, Japan)
  • Uchida, M: Parameter estimation for linear parabolic SPDEs in two space dimensions from discrete observations. Dynstoch meeting 2022 (online), Institut Henri Poincaré, Paris, July 1, 2022
  • Masuda, H.: Formulae for comparing ergodic SDE models (June 30, 2022; Dynstoch meeting 2022, Paris, online)
  • Yoshida, N.: Simplified quasi-likelihood analysis (on-line). DYNSTOCH 2022, Institut Henri Poincaré, Paris, France, June 30, 2022
  • Yoshida, N.: Asymptotic expansion in volatility parametric estimation revisited. Scale Invariance and Randomness, June 8, 2022, Laboratoire Paul Painlevé, Université de Lille, France
  • Kamatani, K.: Non-Reversible Guided Metropolis Kernel. SIAM Conference on Uncertainty Quantification, Atlanta, Georgia, United States (Hybrid), April 12, 2022 (joint work with X. Song)
  • Yoshida, N.: Asymptotic expansion of variations. Seminar - ANR EFFI, April 5, 2022, France, on-line
  • Eguchi, S.: Model comparison for ergodic SDEs in YUIMA. 15th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2022), King's College London(host), UK, December 17-19, 2022.

2021 (Oct 2021 - Mar 2022)

  • Masuda, H.:Estimation and selection of ergodic Lévy driven SDE: an overview of some recent developments. MFO-RIMS Tandem Workshop "Nonlocality in Analysis, Probability and Statistics" (Online (Hybrid)), March 22, 2022.
  • Masuda, H.:Information criteria for ergodic Lévy driven SDE, Workshop: Infinitely divisible processes and related topics" (ISM, Online), November 25, 2021 (joint with S. Eguchi).
  • Kamatani, K.: Scaling limit of Markov chain/process Monte Carlo methods. IASC-ARS 2022, Kyoto, Japan (Hybrid), Febrary 22, 2022 (joint work with J. Bierkens and G. O. Roberts), Keynote Talk

New developments in statistics for
stochastic systems toward data science
for large-scale spatiotemporal dependence

New developments in statistics for
stochastic systems toward data science
for large-scale spatiotemporal dependence

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