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In addition to the traditional chi-square test, the Bollen-Stine bootstrapped version of the test was performed [ 45].
The p-values were computed using the two-sided bootstrapped version of the Kolmogorov-Smirnov test.
The final test included in this comparison is a bootstrapped version of the LHR (Methods, Additional file 1 Methods).
Significant differences in the median CpG-to-gene ratio between the gene sets were determined using the two-sided bootstrapped version of the Kolmogorov-Smirnov test.
We found that the HCNE density was significantly lower for the ST miRNAs (p-value ≤ 0.05, two-sided bootstrapped version of the Kolmogorov-Smirnov test: see Table 1, Figure 2 as well as Additional files 2 and 3).
As shown in Table 1, the HCNE density was significantly higher around ST miRNAs than the random coding and non-coding regions in both comparisons, a trend that is independent of the lineages compared (p-value ≤ 0.05, two-sided bootstrapped version of the Kolmogorov-Smirnov test: see Table 1, Figure 2 as well as Additional files 2 and 3).
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A bootstrap version of the test is also discussed and its performance is evaluated through Monte Carlo simulations.
Step 2: Calculate the Bootstrap version of the statistic of interest (difference of mortality rate and response time).
In the standard bootstrap version of the particle filter, the number of particles in each mode is determined by the posterior probability of that mode.
Moreover, in comparison with the wild bootstrap "version" of the original Breusch Pagan test (Godfrey and Yamagata, 2011) our experiments indicate that the corresponding version of the heteroskedasticity-robust Breusch Pagan test appears reliable.
The particle filter calculates with each measurement the updated particles { x t ( i ), q t ( i ) } i = 1 N p and their weights { w t ( i ) } i = 1 N p from the corresponding previous particles { x t - 1 ( i ), q t - 1 ( i ) } i = 1 N p and weights { w t - 1 ( i ) } i = 1 N p. A single step of the bootstrap version of the MMPF is summarized below.
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