Sentence examples for using the approximate bootstrap from inspiring English sources

23 We calculated confidence intervals using the approximate bootstrap method.

The in-house core-SNP tree was analyzed using the approximate likelihood ratio test, using a selection threshold of 0.8, which is comparable to bootstrap supports of 75% [ 121].

In PhyML, node support was estimated using the approximate likelihood-ratio test (alrt), a much faster method for estimating branch support than either the bootstrap or Bayesian posterior probabilities [48].

The approximate bootstrap confidence algorithm was used to estimate the 95% confidence intervals around the mean cost differences.

Reliability of internal branches was assessed using the bootstrapping method (1 000 bootstrap replicates) and the approximate likelihood ratio test (aLRT – SH-Like) implemented in MEGA and PhyML, respectively [ 52, 53].

The 95% confidence intervals will be estimated using approximate bootstrap confidence (ABC) intervals [ 81].

Using the same bootstrap approach, we obtained approximated 99% confidence intervals for the true differences between the specialization of pairs of transcriptomes, for example Δmn = δm−δn, where m and n are the transcriptomes of interest (normal and cancer tissues), for which the hypothesis of equal specialization (H0: Δmn = 0) needed to be tested.

95% CIs are computed using the bias-corrected bootstrap method using 1000 bootstrap samples.

Topology searches were performed using the fast bootstrap version of the RAxML program, which analyzes 200 bootstrap replicates.

Non-parametric bootstrapping with 5000 replications was used to estimate "approximate bootstrap confidence" (ABC) intervals around cost differences [ 19].

Therefore, bootstrapping with 5000 replications was used to estimate "approximate bootstrap confidence" (ABC) intervals around cost differences [ 32, 33].