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We will be looking at individual cells; we assume that cells in general behave independently, that is, the random variables 's are mutually independent, too.
This justifies the use of WLS for the estimation of LOD and LOQ using the actual experimental data of microarray systems, which generally show heteroskedastic trend, that is, the random variables with different variances according to their concentrations.
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Assuming and, χ=α+β is the random variable of.
where E is the expectation operator and V is the random variable representing the vehicle speed.
where is the random variable modeling the Gaussian noise with mean and a standard deviation of.
where is the random variable of the p.d.f. after SS.
The Pearson correlation coefficients are computed using Eq. (15) where Xk represents the random variable corresponding to the k-th component of the input instance vectors (k = 1,2,) and Y is the random variable representing the class labels.
In what follows x is the random variable over the data sequences to be labeled, y is the random variable over the corresponding label sequences and s is the random variable over the hidden states.
Here, x is the random variable in the first set, and t is the random variable in the remaining three sets.
If N i is the random variable counting the number of occurrences (overlapping or renewal) of a given pattern in X1... X i.
The six degrees of freedom of bone-implant relative position, magnitude of the hip contact force (L), and spatial direction of L were the random variables.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com