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In this study, we propose an approach based on the residual-based bootstrap method to obtain valid prediction intervals using monthly, short-term (three-months) and mid-term (six-months) drought observations.
We used a bootstrap method to obtain confidence intervals [32].
The assumption of multivaraite normality was not met in this data sample, we therefore utilized a bootstrap method to obtain unbiased estimates and standard errors.
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Chen et al. (2004. Ranked Set Sampling: Theory and Applications. Springer, New York) suggest a natural method to obtain bootstrap samples from each row of a RSS.
The 95% CI for the AUROCC values were estimated using the conservative bootstrap bias-corrected and accelerated method to obtain more accurate intervals [ 20].
Choose which method to obtain the eggshell.
There are many well-established methods to obtain confidence intervals from bootstrap replications [ 7, 12].
We adopted the bootstrap method to conduct regression analysis.
We used the percentile bootstrap method (3000 bootstrap re-samples) to obtain 95%% confidence intervals (CI) and considered results to be statistically significant at the 0.05 level if the 95 % CI for measures of association excluded the null value.
Also, a bootstrap method is proposed to obtain critical values.
Differences in ES and SRM between the HHS and the SF-36 were estimated, and the bootstrapping method was used to obtain 95% confidence intervals for these differences.
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