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Maximum likelihood estimation (MLE) was applied to estimate the distribution parameters (Table 1).
The friction method was applied to estimate these costs.
DFRFT is applied to estimate the vibration acceleration.
Finally, FLRLSF is applied to estimate the target state.
Various techniques have been applied to estimate the C-factor.
Recurrent neural networks have been applied to estimate language models.
Structural equation modeling was applied to estimate these relationships quantitatively.
Later, WIPS is applied to estimate future deformations.
For a query peptide, BLAST method was first applied to estimate whether it has antimicrobial activity.
The same methodology was applied to estimate 414,731 unique releasees from state prison in 2003.
Finally, boosting can also be applied to estimate GLMs with sparse priors [42].
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