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However, likewise the FE approach, also the lagged dependent variable model is not free from problems.
A three-stream flamelet/progress variable model is applied to the Sydney piloted premixed jet burner (PPJB).
A physically based state variable model is proposed to simulate precipitate growth encountered in many industry-relevant precipitation processes.
Note also that the dummy variable model is, by construction, the best in terms of explaining the daily pattern of abnormal returns, and therefore the ratio of the two R2 must be between zero and unity.
A two damage state variable model is used to describe the softening mechanisms, damage initiation and growth for a low alloy ferritic steel 1/2Cr 1/2Mo 1/4V at 565 and 590 °C within the Continuum Damage Mechanics framework.
To this purpose, a latent variable model is used to assess the consistency between the correlation structure of a historical operation dataset and that of a similar dataset generated using the FP model.
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In the multiple weather variables model, all significant variables found in the single weather variable model were used in a forward stepwise multiple linear regression analysis, as shown in Table 3.
The Best 3 variable model was then tested on the test dataset.
Accordingly, chicken-zebra finch alignments with ω > 0.5 where the variable model was significantly favoured (p < 0.05) were identified.
These models were compared using a likelihood ratio test (LRT) to determine if the variable model was significantly better at explaining the data [ 13].
We found that a three variable model was able to accurately classify p63 binding sites (sensitivity: 89.8%(±0.3), specificity: 97.6%(±0.02)).
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