Dynamic Modelling of Time-to-Event Processes
Häftad, Engelska, 2025
AvGangaram S. Ladde,Emmanuel A. Appiah,Jay G. Ladde,USA) S. Ladde, Gangaram (Professor, Department of Mathematics and Statistics, University of South Florida, Tampa, Florida,Prairie View A&M University) Appiah, Emmanuel A. (Department of Mathematics,USA) G. Ladde, Jay (Professor, Emergency Medicine, College of Medicine, University Central Florida, Florida, USA. Senior Associate Program Director of Emergency Medicine, Orlando Health, Florida,Gangaram S Ladde,Emmanuel A Appiah,Jay G Ladde,USA) A Appiah, Emmanuel (Assistant Professor, Department of Mathematics, Prairie View A&M University, Prairie View, Texas,USA) G. Ladde, Jay (Professor, Emergency Medicine, College of Medicine, University Central Florida, Florida, USA. Senior Associate Program Director of Emergency Medicine, Orlando Health, Florida
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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.
- Presents a dynamic approach which does not require a closed-form survival/reliability distribution
- Provides updates that are independent of existing Maximum likelihood, Bayesian, and Nonparametric methods
- Applies to nonlinear and non-stationary interconnected large-scale dynamic systems
- Includes frailty and other models in survival analysis as case studies
Produktinformation
- Utgivningsdatum2025-10-23
- Mått152 x 229 x 20 mm
- Vikt450 g
- FormatHäftad
- SpråkEngelska
- SerieAdvances in Reliability Science
- Antal sidor368
- FörlagElsevier Science
- ISBN9780443223433