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In this paper, the bootstrap method was used to estimate the frequency of a signal.
A bootstrap method is used to evaluate the stability of the solution.
For more accuracy, 95%% confidence intervals based on the Bootstrap method was used [14 16].
A bootstrap method was used to select the best subset of risk factors to avoid overfitting the data.
Finally, a bootstrap method is used to determine the influence of the response error on the estimated probability of failure.
The Threshold Bootstrap method is used to model the residential load demand and to produce many realistic load profiles.
Bootstrap method is used to resample the residues with replacement for each θ from the calculated residues.
In addition, the bootstrap method is used to assess the reliability of the network predictions by estimating confidence intervals associated with the results.
This study uses the Koenker (2004) method to perform the panel quantile regression with a fixed effect, while the Bootstrap method is used for the estimate of standard error.
The bootstrap method was used for linear regression analysis of the relationship between the dependent variables (SUVmax, SUVmean, PETvol, TLG, MVD, and size) and the independent variables (BF, BV, and MTT).
For example, reviewed studies failed to report which bootstrap method was used to construct the reported confidence intervals, or did not provide any justification for the number of replications employed.
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