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Fill-in values are obtained from regression models by sampling from LN(β̂ t X i, ς̂). Figure 1C and D show quantile plots of residuals, that is, from exp[log(Z) – β̂ t X]for each subject.

We computed 90,000 structural models by sampling the positions and orientations of the rigid bodies as well as the positions of the remaining beads, guided by the scoring function.

Our model exploration algorithm generated models by sampling features from their posterior probability given the data, through the stochastic selection from the 497-element feature set and calculating the respective logistic regression parameters for subsets of the features (see details below).

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The proposed algorithm firstly constructs the LSSVR localization model by sampling measurement area and training sample sets.

Because very few soil point observations were available within the area, we calibrated the regression model by sampling the soil map on a grid.

To validate the results of the variously presented algorithms, the cross-validation was conducted prior to the permeability modeling by sampling and splitting the data into training and testing subsets.

In Study 3, we tested our hypothesized model by sampling 147 fulltime K-12 teachers who reported their instructional goals on the TGQ and their motivating styles on two separate measures.

Each strategy is characterized by a particular threshold that can be modeled by sampling uniformly from an interval centered on a baseline level.

This shifting in strategy is modeled by sampling from a uniform distribution of usage times, bounded by a minimal (dmin) and a maximal (dmax) usage duration.

We initialize the model by sampling the latent variables from the prior.

Dispersal is then modelled by sampling displacement distances in two dimensions from this distribution (see Bonte et al. 2010).

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