Nakakita M., Nakatsuma T. A hierarchical Bayesian approach for identifying socioeconomic factors influencing self-rated health in Japan. Healthcare Analytics. 2024. 6
Toyabe T., Nakakita M., Nakatsuma T. Bayesian Analysis of Stochastic Conditional Duration Models with Intraday and Intra-deferred Future Seasonalities in High-frequency Commodity Market. Proceedings - 2024 16th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2024. 2024. 305-311
Nakakita M., Nakatsuma T. Hierarchical Bayesian analysis of racehorse running ability and jockey skills. International Journal of Computer Science in Sport. 2023. 22. 2. 1-25
Saito W., Nakatsuma T. Hierarchical Bayesian hedonic regression analysis of Japanese rice wine: is the price right?. International Journal of Wine Business Research. 2023. 35. 2. 256-277
Toyabe T., Nakatsuma T. Stochastic Conditional Duration Model with Intraday Seasonality and Limit Order Book Information. Journal of Risk and Financial Management. 2022. 15. 10
Bayesian analysis of intraday stochastic volatility models with skew heavy-tailed error and smoothing spline seasonality
(Bayesian analysis of intraday stochastic volatility models with skew heavy-tailed error and smoothing spline seasonality 2018)
Bayesian analysis of intraday stochastic volatility models with leverage and skew heavy-tailed error
(11th International Conference on Computational and Financial Econometrics 2017)
Hierarchical Bayes Modeling of Autocorrelation and Intraday Seasonality in Financial Durations
(10th International Conference on Computational and Financial Econometrics 2016)
Hierarchical Bayes Modeling of Autocorrelation and Intraday Seasonality in Financial Durations
(International Society for Bayesian Analysis (ISBA) World Meeting 2016 2016)
Nonlinear Leverage Effects in Asset Returns Evidence from the U.S. and Japanese Stock Markets
(9th International Conference on Computational and Financial Econometrics 2015)
