MC provides a standalone MATLAB-based comprehensive tool for model validation, a task currently performed either ad hoc or implemented in part within other computational tools.
Further, we have been working on adding scaffolding tools (for instance, model tracing and partial model comparison capabilities) to support students in their model validation and debugging tasks.
For example, the coarse approach is more suitable for model validation and benchmarking tasks, where statistical parameters are calculated for certain subsets of data.
This chapter shows how to easily build tools to cover aspects of data exploration, model building, model validation, and model and task management.
One of the main problems in the modeling and simulation of pedestrian movement is the lack of human empirical data that usually limits researchers' understanding of the different behaviors and dynamics of the system and makes the task of pedestrian model validation complicated [8, 9].
Assessing goodness of fit and model validation are, therefore, essential in any model fitting task in general and in constructing predictive models in particular.
A Microsoft Excel/Visual Basic for Applications software has been expressly developed for the latter task that enables automation of the model validation work.
