Advanced Topics
This section is the next layer after Core Concepts. It covers the
cimba.sim features that help larger models stay organized, observable, and
reproducible: components, dynamic processes, per-process fields, explicit
events, timers, trace replay and bootstrap resampling, process graphs,
logging, and reporting.
The snippets continue the clinic and service-desk examples from Core Concepts. They are partial by design. Use them to understand the modeling pattern, then turn to the tutorial and API reference for complete programs and exact helper lists.
- Components
- Structs and Spawnables
- Events, Timers, and Signals
- Data-Driven Traces
- Bootstrapping Methods
- Independent data: the ordinary bootstrap
- Stationary dependent series: block bootstraps
- Trend and seasonality: residual and model-based bootstraps
- State-dependent dynamics: Markov bootstraps
- Scarce data: the parametric bootstrap
- Other methods
- Demand data in supply chains
- Input uncertainty versus stochastic uncertainty
- Writing your own generator
- Process Graphs
- Reporting and Logging
Where this fits
Read Advanced Topics when the basic model shape is already clear and the question has become “how do I keep this model maintainable as it grows?”
For a full worked example of an agent-heavy, resource-heavy model, see Tutorial: Modeling with Cimba Python.