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Theoretical models stability was evaluated by average root mean square deviation (rmsd)/time graph and by overall stereochemical and energy quality.

The model stability was validated using a nonparametric bootstrap (100 samples with replacement).

The phthalic model stability was inferior to 1 h at 80°C whereas the confirmed naphthalenic model one was superior to 100 h in the same conditions.

Information on model stability was provided by studying which combination of predictors occurred most frequently in 2500 data sets.

Model stability was also assessed by calculating the condition number (the ratio of the largest to smallest eigenvalue of the covariance matrix) of the final model, with a value of 1,000 being indicative of ill-conditioning.

The maximum value of forces F O, which did not cause loss of calculation model stability, was considered the maximum occlusion force, generated by the mastication organ muscles in the set dental arch area.

Though, MI is not yet frequently used in predictive modelling and model stability is hardly ever accounted for in MI approaches.

Assumptions about business model stability are no longer true, as new competitors using newer technology create new ways to sell, and often at lower cost than was ever expected.

Model stability is higher, geographic matches are more stable, and the problems due to data dredging are minimized, with models of appropriate complexity.

Identifiability of model parameters and model stability were investigated using the condition number and a bootstrap procedure.

Model stability is also increased by the fact that the size of Vt is not estimated, although it can be inferred in retrospect.