As illustrates, the two trivial models would perform better than the models reported by Guha and Schürer and ourselves, indicating that our models failed at predicting each other.
Trivial models ("All compounds are clean" and "All compounds are toxic") are compared to models developed in this study ("This study") and in reference [11] ("Ref[11]").
Gärdenfors (1988) was specially interested in studying the behavior of his epistemic models when * obeys the constraints of a qualitative version of conditionalization called AGM in the literature.[3] Nevertheless, as Gärdenfors himself points out, there are only trivial models that satisfy these constraints.
As most model fit statistics are sensitive to sample size, statistically significant outcomes may be trivial (models never fit the data perfectly, and even the tiniest deviations can be detected by increasing sample size).
Applying the hierarchical reduction perspective as introduced before (Section 1.2.1), it becomes apparent how quickly very basic cytoskeleton components give rise to highly complex systems that resist trivial modeling attempts.
This paper describes our technique, discusses consistency of model transformations and reports on its application to a non-trivial model transformation from access control models to Java security.
Since typical time-course experiments consists of few time points (5 10 points) (Ernst et al., 2005), fitting any non-trivial model is prone to overfitting.
We have started the application of such technique on non-trivial models provided by biologists and modellers and hope to be able to improve both the understanding, through that identification of fast/slow variables, and the analysis, through the size reduction, of those models.
The downside of this strategy is, of course, that many of your colleagues will tend to assume that an insight that can be expressed in a cute little model must be trivial and obvious — it takes some sophistication to realize that simplicity may be the result of years of hard thinking.
