Sentence examples for bootstrap simulations were used from inspiring English sources

1000 bootstrap simulations were used to test the reliability of branching.

Bootstrap simulations are used to estimate sample uncertainty around the cost-effectiveness ratios and are plotted in cost effectiveness planes, in which the position of the bootstrapped cost-effectiveness pairs gives an indication for possible superiority of one treatment over another.

Bootstrap simulation is used to generate the risk profile savings in vehicle operating cost, and in travel time resulting from demand-responsive traffic.

Bootstrap simulation was used to estimate the standard error for each parameter.

A Jack Knife approach was used to calculate rates and confidence intervals for the binomial count data and bootstrap simulation was used to determine 95% confidence intervals for the detection rate ratios and the number needed to treat.

To determine the corrected P-values on the basis of the maximal χ analysis, 2000 bootstrap-like simulations were used in univariate analyses to estimate the distribution of the maximal χ statistics under the null hypothesis of no association.

All analyses are planned to be carried out with SPSS 19.0 and MLWin 1.10, while bootstrap simulations are done using Excel.

Bootstrap simulations will be used to estimate cost effectiveness acceptability, net benefit statistics and the likelihood that group psycho-education is cost effective compared to group support.

More general methods such as Monte Carlo and bootstrap simulation can be used to estimate the parameter uncertainties.

Similar to the Monte Carlo method, bootstrap simulations are performed 2000 times.

In obtaining bootstrap estimates of the standard errors of each simulation estimate of the population total basal area, 100 bootstrap samples were used; more bootstrap samples might have been used, but some studies of sampling in forest circumstances have suggested that 100 is sufficient (Schreuder et al. 1992; West 2016).