Sentence examples for bootstrap results to estimate from inspiring English sources

We used bootstrap results to estimate median, 2.5th, and 97.5th percentile values for each kinetic parameter in Equations 1 and 2 as well as the ratios Ymax,1: X50,1 and Ymax,2: X50,2, which represent maximum rates of metabolism (micromole per parts per million) for the two pathways (analogous to vmax/ K m), respectively.

To answer these questions, we analyzed the results in the group average results, using a bootstrap to estimate confidence intervals, and separately in the eleven individual subjects in whom both contrasts yielded detectable activations.

We found that applying a bootstrap procedure to estimate the confidence intervals around these predictive values, yields adequate results for the uncertainty in the estimated predictive values.

The bootstrap procedure is not the typical bootstrap to estimate uncertainty on parameters.

We use 10k bootstrap samples to estimate the confidence interval of the correlation coefficient.

A comparison of bootstrap results estimating the mean cross-validated AUC can be seen in Figure 2.

Furthermore, it extends Kriging to random simulation, and discusses bootstrapping to estimate the variance of the Kriging predictor.

Non-parametric bootstrapping was used to estimate the 95% confidence intervals around the estimates.

Bootstrapping was performed to estimate the confidence of the branches using 10 000 neighbour joining replicates [20].

We used multiple sampling (bootstrapping) to estimate 95% confidence intervals.

Bootstrapping is used to estimate the uncertainty surrounding the ICERs.