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These Bayesian procedures make it easy to apply the information gain model to empirical data.

Having parameterized Ψ, f, c and α, and assuming that a is chosen each day to maximize net energy gain, we fit this model to data collected in the field by inferring daily values of κ(t) that minimize the difference between observed and predicted growth given temperature T t) and fish size W t).

5 We illustrated our Bayesian estimation procedure by estimating the parameters of the information gain model using data from a meta-analysis of the Wason task (Oaksford & Chater, 1994).

Researchers can now easily estimate parameters of the information gain model for their own data, using either hierarchical or nonhierarchical specifications.

Due to variability between females, the parameters of the fitness gain models fitted to the data (number of ovipositor insertions against time) were not significantly different between the '8ap' and '8ap + 8ex' patches (Fig. 3), but the rate of ovipositor insertions was significantly affected by the presence of exuviae (Fig. 2).

Finally, by comparing the glider predictions of each model to behavioral data, we can gain insight into which principles underlie Drosophila's known glider responses.

Manual parameter adjustment to fit the model to experimental data is encouraged as a means of gaining insight into model behavior.

To gain more insight into the uni- or bi-dimensionality of optimism and pessimism, we fitted a correlated factor model to the data.

Apply gain table to data (APCAL).

The response gain model, in turn, gave a better fit to the data than the contrast gain model (P = 0.0098, rank sum test).

"They're a way of gaining access to data.

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