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The AV-HMM, denoted as λ a v, is characterized by the state transition probability distribution matrix (A), the observation symbol probability distribution (B), the initial state distribution, a set of N states S = (s1, …, s j, …, s N ), and the audio-visual observation sequence O a v = {oa v 1, …, o a v t, …, o a v T }.
For each given GC-content target distribution, a set of individual target GC values is sampled from the distribution and antaRNA is run for each.
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In order to determine the effects of the variation of the operating conditions on the yield distributions, a set of statistical models were utilized and the maximum point of the yield of each product was determined.
For both distributions, a set of baseline parameter values is required to start the sampling process.
For our purposes the target distribution is the posterior distribution of a set of evolutionary parameters given a set of molecular sequences.
The principle of maximum entropy [26] asserts that the least biased probability distribution satisfying a set of constraints is the maximum entropy distribution, and any other distribution would be assuming information not captured by the constraints.
Thus, the P value can be computed from the joint cumulative distribution of a set of uniformly distributed order statistics.
The Kernel Density Estimation (KDE) is a non-parametric approach to estimate the probability density of a distribution given a set of n samples drawn from this distribution and a kernel function k.
The distribution of a set of associated factors with respect to a disease was modeled as a tri-modal distribution: a distribution which has three modes.
We assume that the insert size distribution in a set of reads R can be modeled by the normal distribution with known mean μ and standard deviation σ.
Since this distribution returns a set of complex numbers, we assess the cross time-frequency analysis using the real part of the distribution.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com