Surprisingly, the moment ratios (given in eq. (4)), which display fluctuations of the distance distributions, exceed the random walk value for looping probabilities <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0012218.e221.PNG" class= inline-graphic"/> in the range where a leveling off in the mean square distance is observed.
The number of our simulated Zipf distributions exceeds the size of published immune repertoire HTS datasets by one to two orders of magnitude [ 7, 10, 16].
The significance P of an original cluster was estimated according to the proportion of the randomization null distribution exceeding the observed maximum/minimum t-sum test-statistics.
By creating a distribution from 100 random sets of permutation, statistical significance (p < 0.05) was estimated as the proportion of elements in the randomization null distribution exceeding the observed maximum-cluster level test statistics.
In contrast, those tags with a copy number between 2 and 5 showed a broad distribution (exceeding 50%) of distinct clean tags (Additional file 3: Figure S3).> To determine whether the depth of deep sequencing is sufficient, we performed a sequencing saturation analysis (Additional file 4: Figure S4).
%MinMax values for which the sum of the difference from the ideal distribution exceeded ten percent were determined to be not normally distributed; this assignment occurred primarily in the extreme %Min region, where populations of random reverse translations would be required to contain almost exclusively the rarest codon for each amino acid, a statistically unlikely event.
If your distribution exceeds the demand you created, it will result in unsold inventory.
What needs special mention is that the delivery rate calculation of QMOR including the distribution exceeds the delay constraint.
The antibiotic resistance development risk (RDR) for each antibiotic was calculated as the probability that the antibiotic exposure distribution exceeds the MSC distribution representing the bacterial community.
For each combination of network and controller set, up to 250 episodes were simulated for learning purposes, each starting from a randomly generated state within a Hellinger distance of 0.01 of the target distribution and ending if the distance between the state and target distribution exceeded the specified Hellinger threshold.
