Online edition: ISSN 2432-6380
[TOP] | [2020] | [2021] | [2022] | [2023] | [2024] | [2025] | [2026] | [Japanese] / [English]
R2025-32
Evaluation of confidence interval constructed using the modified Wald statistic
Yuto Yamamoto, Ueki Masao (Nagasaki Univ.)
pp. 1 - 3
R2025-33
AUC Maximization in Binary Classification Models and Its Robustness Evaluation
Taichi Sakuma, Tetsuji Ohyama (Kurume Univ.), Takeshi Emura (Hiroshima Univ.)
pp. 4 - 6
R2025-34
A note on sports injury prediction model for sumo wrestlers with dependent censoring by retirement
Shuhei Ota (Kanagawa Univ.), Mitsuhiro Kimura (Hosei Univ.)
pp. 7 - 11
R2025-35
Methodology for Multiple Imputation in Survival Analysis
-- Compatibility between the Substantive and Imputation Models --
Masato Iwami, Frukawa Kyoji (Kurume Univ), Takeshi Emura (Hiroshima Univ)
pp. 12 - 15
R2025-36
A Basic Study of Factor Analysis under Dependent Termination
-- Framework for survival time analysis using copulas and exponential distributions --
Rikuto Takatani, Takeshi Emura (Hiroshima Univ.)
pp. 16 - 30
R2025-37
Joint Frailty-Copula Model for Simultaneous Analysis of Overall Survival and Progression-Free Survival in Lung Adenocarcinoma
Ayano Kajitani, Takeahi Emura (Hiroshima)
pp. 31 - 37
R2025-38
A Note on EM Estimation for Bernstein Copula with Binned Data
Hiroyuki Okamura, Junjun Zheng, Tadashi Dohi (Hiroshima Univ.)
pp. 38 - 41
R2025-39
Kota Izumi (Kitasato Univ.), Takeshi Emura (Hiroshima Univ.), Hirofumi Michimae (Kitasato Univ.)
pp. 42 - 47
R2025-40
Estimating mixture ratio for the mixture distribution
-- Toward applications to the stochastic timed automata --
Nanami Taketomi (Nagasaki Univ.)
pp. 48 - 51
R2025-41
On new metrics IAP and IRP for binary classification tests without a gold standard
Tetsuji Ohyama (Kurume Univ.)
pp. 52 - 56
R2025-42
[Invited Talk]
Prediction intervals and their application to reliability with statistical models
Masao Ueki (Nagasaki Univ.)
pp. 57 - 60
Note: Each article is a technical report without peer review, and its polished version will be published elsewhere.