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Second, we analyze the spatial resolution of slip with respect to input data by performing a bootstrap analysis (with variable Vr), in which we randomly select 116 'new' data from the 116 input data, and reinvert.
The tree topologies were evaluated by performing a bootstrap analysis with 1,000 replicates.
Empirical P values were calculated by performing a bootstrap where gene labels were shuffled 10,000 times and the enrichment was recalculated.
We estimated the variance of these measures by performing a bootstrap analysis (Efron 1979) over sets of functional maps grouped by experiment and subsequently estimating confidence intervals (CIs) for the measured distributions.
Statistical significance was tested by performing a bootstrap with 1000 iterations on the paired power data, taking the 97.5% percentile of these resampled values, and testing whether its absolute value was larger than the correlation computed on a randomly shuffled set of times.
This null distribution of PCCs was derived by performing a bootstrap procedure randomly selecting four (for the 'identical' analysis corresponding to four cell types) or eight (for the 'common' analysis corresponding to five cell types) promoters from the transcriptome and translatome dataset (in total 19 promoters and ten promoters, respectively, see Supplementary Data Table S1).
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We assess the robustness of our results by performing a bootstrapping procedure in which we randomly sample 10% of subjects and their network connections with replacement 5,000 times to assess the distribution of our paradox indicators for different samples of our network.
The significance of OOB classification errors was determined by performing a further 1,000 bootstrap replicates of each model with random permutations of the classification variable.
Double BOOT offers a solution to this problem by performing a second layer of bootstrapping that uses a bootstrap data-generating process to weight each of the original candidate models according to their prevalence (measured through w i) as "best" models among the original B bootstrap replicate series.
Confidence intervals for the statistic were found by performing a large number of bootstraps, where in each bootstrap reference genes were sampled with replacement in the denominator and numerator separately [ 50], and recomputing the statistic for each bootstrap.
An example of computing the confidence bands for PRC by performing a standard non-parametric bootstrap at each time point (weekly data were used) is given in [8].
More suggestions(16)
by applying a bootstrap
by performing a review
by adopting a bootstrap
by performing a range
by performing a funnel
by performing a breadth
by performing a search
by performing a traceback
by performing a protein-by-protein
by performing a thought
by performing a permutation
by performing a bulldog
by performing a voxel-wise
by performing a covariance
by performing a cost
by performing a clothesline
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