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Full Description
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.
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
