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141 to 150 of 258 Results
Count Data for Sui Jingji zhi 隋經籍志, Hanshu Yiwen zhi 漢書藝文誌 and Bianzheng lun 辯正論
May 19, 2026 - Michael STANLEY-BAKER
Stanley-Baker, Michael, 2026, "Count Data for Sui Jingji zhi 隋經籍志, Hanshu Yiwen zhi 漢書藝文誌 and Bianzheng lun 辯正論", https://doi.org/10.21979/N9/MVPBRH, DR-NTU (Data), V2, UNF:6:qHIwT1Q3h1MPKit7FE/olg== [fileUNF]
Count of titles in two imperial bibliographies and a Daoist Catalogue. Statistical evidence for distribution of knowledge types in the three works.
Replication Data for: Tsunami Hazard Assessment for Singapore and the Sunda Shelf RegionEmbargoed
May 15, 2026 - TAN Elaine Hui Zhi
Tan, Elaine Hui Zhi, 2028, "Replication Data for: Tsunami Hazard Assessment for Singapore and the Sunda Shelf Region", https://doi.org/10.21979/N9/DCKJWW, DR-NTU (Data), V1
This dataset comprises the data files and model setup files used to generate the simulations presented in the thesis, Tsunami Hazard Assessment for Singapore and the Sunda Shelf Region, in support of the reproducibility of the research.
TAN Elaine Hui Zhi (Nanyang Technological University)
May 15, 2026Asian School of the Environment (ASE)
Replication data for: Physicochemical-informed predictive modelling on small datasets for designing conductive polymer inks in soft bioelectronics
May 14, 2026 - Jia Min LEE
Lee, Jia Min, 2026, "Replication data for: Physicochemical-informed predictive modelling on small datasets for designing conductive polymer inks in soft bioelectronics", https://doi.org/10.21979/N9/WC4D7J, DR-NTU (Data), V1, UNF:6:S0x4Y5WE079p7+0mwh5wgg== [fileUNF]
Dataset for physico surrogate model.
Replication Data for: Disease progression based feature screening for ultrahigh-dimensional survival-associated biomarkers
May 12, 2026 - Liming XIANG
Xiang, Liming, 2026, "Replication Data for: Disease progression based feature screening for ultrahigh-dimensional survival-associated biomarkers", https://doi.org/10.21979/N9/OSRVWN, DR-NTU (Data), V1
This dataset contains the R code for simulation studies reported in the paper "Disease progression based feature screening for ultrahigh-dimensional survival-associated biomarkers".
Replication Data for: Analysis of Competing Risks Data with Covariates Subject to Detection Limits
May 12, 2026 - Liming XIANG
Xiang, Liming, 2026, "Replication Data for: Analysis of Competing Risks Data with Covariates Subject to Detection Limits", https://doi.org/10.21979/N9/NNUDA2, DR-NTU (Data), V1
This dataset contains a set of simulated data and the R code for simulation studies reported in the paper "Analysis of Competing Risks Data with Covariates Subject to Detection Limits".
Replication Data for: Regression analysis of interval-censored competing risks data with missing causes of failure: a direct likelihood approach
May 12, 2026 - Liming XIANG
Xiang, Liming, 2026, "Replication Data for: Regression analysis of interval-censored competing risks data with missing causes of failure: a direct likelihood approach", https://doi.org/10.21979/N9/MPYZO1, DR-NTU (Data), V1
This dataset contains the MATLAB code used to generate the simulation results reported in the paper "Regression analysis of interval-censored competing risks data with missing causes of failure: a direct likelihood approach".
Replication Data for: Flexible modeling of left-truncated and interval-censored competing risks data with missing event types
May 12, 2026 - Liming XIANG
Xiang, Liming, 2026, "Replication Data for: Flexible modeling of left-truncated and interval-censored competing risks data with missing event types", https://doi.org/10.21979/N9/HCO7AV, DR-NTU (Data), V1
This dataset contains the MATLAB code used to generate the simulation results reported in the paper "Flexible modeling of left-truncated and interval-censored competing risks data with missing event types".
Replication Data for: Learning association from multiple intermediate events for dynamic prediction of survival: an application to cardiovascular disease prognosis
May 12, 2026 - Liming XIANG
Xiang, Liming, 2026, "Replication Data for: Learning association from multiple intermediate events for dynamic prediction of survival: an application to cardiovascular disease prognosis", https://doi.org/10.21979/N9/TQODZO, DR-NTU (Data), V1
This dataset contains simulation results and R code used to generate the results in the paper "Learning association from multiple intermediate events for dynamic prediction of survival: an application to cardiovascular disease prognosis".
Liming XIANG(Nanyang Technological University)
Liming XIANG logo
May 12, 2026School of Physical and Mathematical Sciences (SPMS)
Dr. Xiang Liming's areas of expertise are survival analysis, longitudinal/clustered data analysis, mixture modelling and biostatistics. Her current research work focuses on developing semiparametric methods for analysis of survival data subject to complex censoring that arises in...
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