Hi,
I am building an agent-based simulation,
There is no real data to construct the model, a data is used to generate some values helo to define agents' decision making. There is also some randomness added to the model. I need to know the best methods that allow me to design experiments and quantify uncertainty.
I should run a sensitivity analysis to fully understand the dynamics of the model since I don't have real data for validation, but I don't have a solid statistical background.
Some questions:
Nada
I am building an agent-based simulation,
There is no real data to construct the model, a data is used to generate some values helo to define agents' decision making. There is also some randomness added to the model. I need to know the best methods that allow me to design experiments and quantify uncertainty.
I should run a sensitivity analysis to fully understand the dynamics of the model since I don't have real data for validation, but I don't have a solid statistical background.
Some questions:
- How do I know the required number of repetition of the simulation?
- Most of the modellers consider sensitivity analysis to analyze model output, but I don't know what techniques in sensitivity analysis are proper?
- How can I select more representative visualizations to show the results?
Nada