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In most cases, estimation of rock mass parameters and in situ stresses using empirical methods are not accurate enough.
In some cases, estimation of the 95% highest posterior density confidence intervals was not possible given the low node support.
In other cases, estimation of the generation time distribution is relatively straightforward from pairs of infectors/infectees if there is a marked separation between generations; it is more complicated when generations quickly overlap as with influenza [ 23].
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In such cases, estimations of the FDG dosage injected prior to halting administration may be helpful.
In such cases, estimations of the FDG dosage injected prior to halting administration may be helpful in making a decision on how to proceed, whether to perform venipuncture at a different site to inject additional FDG or to estimate the eventual influence of underdosing on standardized uptake values (SUVs) and image quality [4 6].
This property is especially useful when there is only one item available, in which case estimation of C α or ρ is impossible by definition.
The latter is because the posterior of the SNP effects may be bimodal [ 10], in which case estimation of the mode does not make much sense (both modes may be quite far away from the mean).
In this case, estimation of precision can be performed before implementation (eg, ±1 bp), whereas trueness is dealt with by running a standard curve with each experiment (ie, a size standard).
In this case, estimations of expected long-term changes in the planetary distribution of cutoff rigidities, which also influence CR intensity, as well as CR-influenced effects on global climate variation, become important.
The results have to be considered as best case estimations of DT50 for several reasons: they only reflect the warmer period of the year; 3 years passed between (first) application and measurements, therefore potentially allowing microorganisms to adapt; only dissipation was monitored including all possibilities of substance losses, and finally NERs were not considered at all.
In all cases, the estimation of evolutionary distances is subject to inference uncertainty, which is commonly quantified by their variances and covariances.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com