Sentence examples for model averaging technique from inspiring English sources

We then combined forecasts from multiple candidate DWT SVR models using a model averaging technique based upon Akaike's information criterion (AIC).

This model averaging approach is more simple to compute requiring only to fit a simple multiple linear regression model, unlike the VWA approach in which the weighting is estimated for each soil property, and thus in the interests of parsimony is recommended as the model averaging technique to be adopted as protocol.

Finally, gradient boosting regression tree models, which are a model averaging technique, were examined to determine whether a better prediction could be achieved using a more complex algorithm.

This is most likely due to the fact that BVSA implements a model averaging technique, which determines the network topology by averaging a set of likely network models, whereas LMML and SBRA implement two different model selection techniques, each of which find a single network model that maximizes a likelihood function.

Structural damage is then identified using Bayesian model class selection and model averaging techniques over the results of all the considered model updating classes.

Therefore, integrating model averaging techniques with the hybrid DWT SVR model would be a promising approach for daily and monthly streamflow forecasting.

Combining model outcomes derived from spectra using model averaging techniques improves or maintains the prediction status (as ratio of performance to inter-quartile distance) of vis-NIR and XRF models for a wide range of soil properties of agronomic importance.

Sparse point and/or interval data regarding the input random variables leads to uncertainty regarding their distribution types, distribution parameters, and correlations; this statistical uncertainty is included in the reliability analysis through a combination of likelihood-based representation, Bayesian hypothesis testing, and Bayesian model averaging techniques.

Randomness of design variables is modeled through local averaging technique followed by Cholesky decomposition for digital simulation.

Multiple grain interactions are modeled applying an averaging technique, embedding grains into an effective electromechanical medium.

To test this correspondence further, we also developed a hybrid model that bridges the averaging technique of PG with the VPG in a linear weighted fashion so a gradual transition from one model to the other can be analyzed [ 30].