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A regression model with only confidence as a predictor (BIC = 282) was also better at predicting task choices than the reduced model with only accuracy and RTs (BIC = 310).
In subsequent calculations, we therefore used the regression model with only energy density to predict litter size.
An assumption of homogeneity enables the solution of the hybrid model with only a slight error.
To demonstrate this we consider a model with only one exogeneous variable, generalizations being obvious.
Next, a model with only a long capillary tube passage (an inertia track) is examined.
A simple model with only one fitting parameter was selected to compare with the experimental data.
Finally, the null model with only technical noise was rejected for 71 out of the 73 features, often with very high evidence (median 69.6 bits).
Adding electrocardiogram variables to the prediction model with only clinical predictors significantly improved the area under the receiver operating characteristic curve, from 0.71 to 0.78 (p<0.78).
The behavior of a model with only one intermediate state and a model describing a molecular zipper is studied.
The simple model, with only a few adjustable parameters, provides a good description of the thermodynamic properties for this system.
An improved mass model with only two parameters for coarse coal particles using image analysis was established.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com