Sentence examples for bootstrap technique to estimate from inspiring English sources

We used bootstrap technique to estimate the standard error (SE) and 95% confidence interval (CI) for the RVs [ 20]–[ 26].

It uses a numerical bootstrap technique to estimate the confidence interval of the risk probability associated with an integer score [ 14- 16].

However, in the general case when more data are available and it is not clear what sample size to use in the bootstrap for a given Λ, one can combine parametric and nonparametric bootstrap techniques to estimate the sample size and the bias.

To assess the validity of the risk scores, we used bootstrapping techniques to estimate a 'confidence interval' (bCI) around the estimated AUC of all risk scores in our population.

Given the computational burden, we applied the bootstrap resampling technique to estimate the standard deviation and the confidence interval (CI) for the optimal cut-point for some selected scenarios with sample size N = 100 or N = 150.

Bootstrapping is a technique to estimate the variance, that is, to approximate the sampling distributions of the statistic.

After using a bootstrapped data envelopment analysis technique to estimate efficiency scores for each hospital in our sample [ 5, 6], we employed propensity score matching to ensure that the two groups of hospitals in our analysis (i.e. privatized and non-privatized) were comparable in terms of organizational characteristics, environmental characteristics, and patient heterogeneity [ 7– 9].

83, 231 241] have given their re-scaling bootstrap technique to construct confidence interval and to estimate mean square error for non-linear functions of finite population totals of several real variables.

Standard errors for the observed N positive and observed N negative were estimated using a bootstrap technique to generate many sets of simulated data to which the negative binomial function was fitted and the standard error calculated for the simulated N positive and the simulated N negative for each AUDIT score.

In such situation, we propose to use bootstrap technique to obtain enough data.

After calculating path estimates in the structural model, PLS utilized a bootstrapping technique to acquire the corresponding t-values.