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Most methods assume the layout of the air distribution system to be predetermined and focus solely on the sizing of each fan and duct in the network.
In the case of tracking moving targets, most methods assume that each source angle is constant during a time interval.
For example, most methods assume that the mRNA level of a regulator is a true indication of its activity, and that there is no time lag or a constant time lag between the transcription of a regulator and the transcription of its target genes.
This is because most methods assume that variances of clusters are similar to one another.
This is problematic since most methods assume there exists a common set of driver genes.
Most methods assume that P-values are continuous and uniformly distributed on (0, 1) under H0.
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Most discounting methods assume that the distance between bodies of evidence is the only factor for conflict estimation.
Most other methods assume that the stress drop of the synthesized earthquake is the same as that of the EGF.
Most other methods assume the geometry of the handle is already known and the vision systems are just used to locate.
This is because implicitly, most estimation/training methods assume for the univariate approach that the variance of the error is constant whereas the multivariate approach allows for variation over the day.
In addition, most retinex methods assume that the estimated error between observed image and the product of reflectance and background illumination is a random variable with a Gaussian distribution with zero mean and variance δ 2. The maximum likelihood estimation (MLE) solution of Gaussian distribution is equivalent to the solution of ordinary least squares (OLS).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com