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Even though the earlier discussion assumed that the error caused by the symbol level limiter is purely additive, we will adopt an another model for the channel estimator modifications.
It is worth mentioning that condition (A1) is much weaker than those in the literature where it is commonly assumed that the error term has Gaussian tail probability distribution.
In these studies, it is implicitly assumed that the error terms within or between profiles is independently and identically normally distributed; however in some cases, these assumptions can be violated.
We assumed that the error of equals to 5%.
Our primary exposure models assumed that the error terms exhibited spatial correlation that could be modeled with a kriging variogram parameterized by a vector of parameters θ⊇= (Cressie 1992).
Since the BMI of these subjects was just over average at 26.6 kg/m, it was assumed that the error of magnification at 4% would be inconsequential to x-ray accuracy for the purposes of this study.
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Here, we have assumed that the errors of observational and model parameters follow Gaussian distributions.
It may be assumed that the errors in volume / biomass for subsample trees are negligible, but not for the tally trees.
Many assumed that the errors in DNA replication are biased toward different directions in different bacteria.
We assumed that the errors followed a lognormal distribution with geometric means equal to the model-predicted concentrations of plasma E2, T, and VTG, respectively.
In all the cases, it was assumed that the errors were normally distributed with zero mean and in the cases of IND and AR1, the error variances were fixed over time and equal to σ 2 = 0.5.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com