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The topology of the distance tree was tested by resampling data with 1000 bootstraps to provide confidence estimates.
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Figure 1 illustrates the data structure of the final results of all interested pharmacokinetic parameters, which were calculated by creating multiple simulated data sets and refitting models with resampling data.
In this analysis, we randomly resampled 1/32 to 1/2 (increasing by twofold) of total reads and using these resampled data sets with smaller size we screened for single-base substitutions using the identical algorithm as used in Table 4. Figure 2 shows true positive and false positive/negative rates as functions of mean coverage.
For each lens, 100 average samples were generated in this way, followed by division of the 63× resampled data by the 100× resampled data.
With the resampled data, reaction norm midpoints (Lp50) were calculated by means of the process described above.
In all cases, bootstrap analysis was performed with 1,000 resampled data sets.
We assessed the significance of the model coefficients by resampling 10,000 times with replacement, fitting the model to the resampled data, and generating 95%, 99%, and 99.9% confidence intervals using the corresponding quantiles of the coefficient distributions.
Finally, accurate diagnosis for train bearing faults can be achieved by applying conventional spectrum analysis techniques to the resampled data.
We have estimated the confidence intervals of the parameters by resampling the bilateral FOF trials and fitting the model to this resampled data.
Bootstrap values represent 1,000 resampled data sets.
The nonparametric bootstrap diagnostics (n = 1,000) were stratified by drug administration with or without food to maintain an equal distribution of patients in the resampled data.
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