Dynamic Modelling of Time-to-Event Processes covers an alternative dynamic modelling approach for studying time-to-event processes. This innovative approach covers some key elements, including the Development of continuous-time state of dynamic time-to-event processes, an Introduction of an idea of discrete-time dynamic intervention processes, Treating a time-to-event process operating/functioning under multiple time-scales formulation of continuous and discrete-time interconnected dynamic system as hybrid dynamic time-to-event process, Utilizing Euler-type discretized schemes, developing theoretical dynamic algorithms, and more.
Additional elements of this process include an Introduction of conceptual and computational state and parameter estimation procedures, Developing multistage a robust mean square suboptimal criterion for state and parameter estimation, and Extending the idea conceptual computational simulation process and applying real datasets.
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Table of Contents
1. Some Latent Dynamic Structural Elements in Time-to-Event Processes
2. Linear Deterministic Hybrid Dynamic Modeling of Time-to-event Processes (LDHDM)
3. Conceptual Computational and Simulation Algorithms
LDHDM
4. Nonlinear Deterministic Interconnected Hybrid Dynamic Modeling for Time-to-Event Processes
INHDMTTEP
5. Conceptual Computational and Simulation Algorithms for INHDMTTEP
6. Stochastic Hybrid Dynamic Modeling for Time-to-event Processes
SIHDMTTEP
7. Conceptual Computational and Simulation Algorithms for SIHDMTTEP
8. Application to Time-to-Event Datasets
9. Statistical Comparative Analysis with Existing Methods
10. Case Studies

