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Rather than splitting data into test and validation sets, we performed a cross-validation, that uses repeated data-splitting to prevent model overfitting and to generate accurate estimates of model coefficients, being a compelling statistical technique for model validation [14].
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The principal h-d models also vary on how the model coefficients are being interpreted, which is especially important if they are then modelled as smooth functions of predictors.
Many of the VAR model coefficients were not statistically significant.
The MNL model coefficients are difficult to interpret.
The related model coefficients are determined with measurable parameters.
Model coefficients are developed using ordinary least squares (OLS) regression.
The model coefficients are identified in terms of measurable parameters.
All model coefficients were obtained from literature data.
The physical implications of the model coefficients are also discussed.
Model coefficients are calibrated for each month using historical data.
(4) The AR model is constructed and model coefficients are saved for user verification.
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