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Rather than use a bootstrap approach which would resample from actual CFS, we instead use an empirical fit of the distributions of the CFS in space and time.
We did not use a bootstrap approach, because running bootstraps is often less intuitive for a policy and health plan audience and requires intensive computer resources.
For this benchmark experiment, we did not use a bootstrap approach, because the original study did not report the ethnicities and gender information for each individual and as a result we cannot re-create a balanced experimental sampling design using bootstraps.
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Field-significance was tested using a bootstrap approach.
Hosseinzadeh et al. (2016) identified the importance of a balance of efficiency gains and losses for 33 Australian mining firms by using a bootstrap approach.
The idea of using a bootstrap approach to simulate on environmental data to financial outcomes, including the repayment time and CFaR metrics chosen here, is generally applicable.
The idea is to extend the EM algorithm using a bootstrap approach but also allowing for the incorporation of priors on model parameters.
We used a bootstrap approach to explore parameter uncertainty.
As earlier, this result was confirmed using a bootstrap approach (P = 0.0073 and P = 0.0039, respectively).
We can then compare this score with an expected value obtained using a bootstrap approach; the method is explained in detail in the results section.
The fourth method uses a bootstrap approach.
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