Friday, December 30, 2011


Model structure--the relationship between model elements.

Calibration--using data-sets to ensure that model matches. Differences between these two constitutes specification error.

Validation --Tests to measure  models predictive capacity. Requires a second data-set.

Model Development Principles
•    Concentrate on transparency. Models should be communicable. This necessitates the development of nested modeling.
•    Limit interconnectivity between model elements to the minimum possible.
•    Model structure should be transparent. Relationships between model elements shoul be clear, and should (when possible) correspond to participants pre-existing mental categories.
•    Equations available, data-sources documented. When possible, a model should be packaged to contain it's own documentation.

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