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1 to 10 of 666 Results
SI Data for: Pixelated quantum-dot superlattice LEDs
Jun 11, 2026 - YU Yue
Yu, Yue, 2026, "SI Data for: Pixelated quantum-dot superlattice LEDs", https://doi.org/10.21979/N9/HOOWBQ, DR-NTU (Data), V1, UNF:6:ny+BFtTVo3ZS+Kc8ueRn+Q== [fileUNF]
Replication SI Data for the journal article entitled "Pixelated quantum-dot superlattice LEDs "
YU Yue(Nanyang Technological University)
Jun 11, 2026
Replication Data for: Giant Photon Superbunching from Weak Nonlinearity
Jun 5, 2026 - WANG You
Wang, You, 2026, "Replication Data for: Giant Photon Superbunching from Weak Nonlinearity", https://doi.org/10.21979/N9/WXV9BM, DR-NTU (Data), V1
Computer code used to generate the simulation plots presented in the paper Giant Photon Superbunching from Weak Nonlinearity.
Related Data for: Ferron-driven photoferroic hysteresis in van der Waals CuInP2S6
May 24, 2026 - Sambhu JANA
Jana, Sambhu, 2026, "Related Data for: Ferron-driven photoferroic hysteresis in van der Waals CuInP2S6", https://doi.org/10.21979/N9/UYX5YD, DR-NTU (Data), V1
All the data related to the paper titled “Ferron-Driven Photoferroic Hysteresis in Van der Waals CuInP₂S₆” have been uploaded here.
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, 2026
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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