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Applications include searches over reaction databases with unknown drawing models, and comparison of reaction databases with different drawing models.
None of the parameters is perfect and can be individually applied for identification of adequate data visualization models and comparison of different maps.
Analysis of sinusoidal noisy leaky integrate-and-fire models and comparison with experimental data are important to understand the neural code and neural synchronization and rhythms.
An in-depth discussion of linlog models and comparison with other approximative rate functions can be found in the review by Heijnen (2005).
Additionally, stepwise analysis was performed to assess the effect of potential confounders including village, age, sex, and hookworm infection on all models, and comparison between models was performed by using likelihood ratio tests.
The modelling process had three main stages: (i) selection of mouse genotypes with retinotopic map data; (ii) selection of models from the literature to test against the data, and (iii) simulation of these models and comparison with the data.
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It is important not to take linear models and comparisons of living species too far.
Some validation examples of the developed models, and comparisons among different mooring approaches, are presented.
A new criterion, TE-optimality, is defined, based on the difference in the deviances from the two models, and comparisons are made with T-, Ds- and D-optimality.
Out-of-sample prediction tests of the density and time occupancy models and comparisons with pedestrian count data from field observations indicated substantial predictive accuracies.
Other models and comparisons could be considered but we found these to be sufficient for illustrating the differences among centers.
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predictions and comparison
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