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Fingerprint Dive into the research topics where Hiroki Masuda is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Stable Process Mathematics
Ornstein-Uhlenbeck Process Mathematics
Quasi-likelihood Mathematics
Jump Mathematics
Stochastic Equations Mathematics
Estimator Mathematics
Differential equation Mathematics
Edgeworth Expansion Mathematics

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Research Output 2004 2019

  • 315 Citations
  • 9 h-Index
  • 28 Article
  • 1 Comment/debate
1 Citation (Scopus)

AIC for the non-concave penalized likelihood method

Umezu, Y., Shimizu, Y., Masuda, H. & Ninomiya, Y., Apr 1 2019, In : Annals of the Institute of Statistical Mathematics. 71, 2, p. 247-274 28 p.

Research output: Contribution to journalArticle

Penalized Likelihood
Information Criterion
Likelihood Methods
Penalized Maximum Likelihood
Model Selection

Bayesian inference for stable Lévy–driven stochastic differential equations with high-frequency data

Jasra, A., Kamatani, K. & Masuda, H., Jun 1 2019, In : Scandinavian Journal of Statistics. 46, 2, p. 545-574 30 p.

Research output: Contribution to journalArticle

High-frequency Data
Bayesian inference
Stochastic Equations
Differential equation
Metropolis-Hastings

Data driven time scale in Gaussian quasi-likelihood inference

Eguchi, S. & Masuda, H., Oct 15 2019, In : Statistical Inference for Stochastic Processes. 22, 3, p. 383-430 48 p.

Research output: Contribution to journalArticle

Likelihood Inference
Quasi-likelihood
Data-driven
Model Selection
Time Scales
1 Citation (Scopus)

Non-Gaussian quasi-likelihood estimation of SDE driven by locally stable Lévy process

Masuda, H., Mar 1 2019, In : Stochastic Processes and their Applications. 129, 3, p. 1013-1059 47 p.

Research output: Contribution to journalArticle

Quasi-likelihood
Stable Process
Maximum likelihood
Stochastic Equations
Quasi-maximum Likelihood
1 Citation (Scopus)

Efficient estimation of stable Lévy process with symmetric jumps

Brouste, A. & Masuda, H., Jul 1 2018, In : Statistical Inference for Stochastic Processes. 21, 2, p. 289-307 19 p.

Research output: Contribution to journalArticle

Efficient Estimation
Stable Process
Likelihood
Jump
Local Asymptotic Normality