J-GLOBAL ID:201601009162887590   Update date: Sep. 20, 2021

Tsukuda Koji

Tsukuda Koji
Affiliation and department:
Papers (14):
  • Koji Tsukuda, Shun Matsuura. Limit theorem associated with Wishart matrices with application to hypothesis testing for common principal components. Journal of Multivariate Analysis. 2021. 186. -. 104822
  • Koji Tsukuda, Yoichi Nishiyama. Weak convergence of marked empirical processes in a Hilbert space and its applications. Electronic Journal of Statistics. 2020. 14. 2. 3914-3938
  • Koji Tsukuda, Hiroshi Kurata. Covariance structure associated with an equality between two general ridge estimators. Statistical Papers. 2020. 61. 3. 1069-1084
  • Bayesian approach to discriminant problems for count data with application to a multilocus short tandem repeat dataset. Statistical Applications in Genetics and Molecular Biology. 2020. 19. 2
  • Koji Tsukuda. Error bounds for the normal approximation to the length of a Ewens partition. Pioneering Works on Distribution Theory: In Honor of Masaaki Sibuya. 2020. 55-73
MISC (4):
  • Koji Tsukuda. Evaluating moments of length of Pitman partition. arXiv. 2021. 2008.12472v4
  • 佃 康司. 前期課程に所属する学生の学修行動の経年変化について. 東京大学 教育研究データ分析室紀要. 2019. 2. 12-30
  • Koji Tsukuda, Shuhei Mano. A reversal phenomenon in estimation based on multiple samples from the Poisson--Dirichlet distribution. arXiv. 2018. 1802.00578
  • 佃 康司. 動特性パラメータ設計における標本SN比の漸近的性質に関する研究. 品質. 2015. 45. 3. 247-249
Lectures and oral presentations  (7):
  • Fluryの共分散行列モデルに対する高次元二標本検定の検討
    (2021年度統計関連学会連合大会 2021)
  • A change detection procedure for an ergodic diffusion process
    (13th International Conference on Computational and Financial Econometrics (CFE2019) 2019)
  • Goodness-of-fit tests for Markovian processes based on marked empirical processes
    (3rd International Conference on Econometrics and Statistics (EcoSta 2019) 2019)
  • An Error Bound for the Normal Approximation to the Length of a Ewens Partition
    (Pioneering Workshop on Extreme Value and Distribution Theories In Honor of Professor Masaaki Sibuya 2019)
  • ノイズ共変量に対するロバストパラメータ設計
    (第9回 横幹連合コンファレンス 2018)
Professional career (1):
  • Ph.D. (SOKENDAI, the Graduate University for Advanced Studies)
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