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This may typically occur if one combines information from multiple samples, which can, e.g. be related to further aspects of units that define the samples or groups to which the units belong or to different applications where the circumstances under which the units operate can vary.
The standardization of the methodology made it possible to define the samples evenly, recreating the same conditions of data acquisition for all the subjects.
We define the samples in the different columns as explained earlier in the note, so in some cases the share of observations in a range can substantially exceed or fall short of the strict definition.
Firstly, we introduce some concepts to define the samples.
In this case, because the copy number status of each gene is available besides the list of somatic SNVs and short indels (hereinafter, mutations), I employed both types of alterations to define the samples where each driver TF is altered.
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Moreover, it is also utilized to define the sampling area.
We use both solutions and the Green's matrices to define the sampled transforms.
Then, from the given Eq. 6, we can define the sample vector form, which is: (7).
In addition, it was difficult to define the sample position and the material quality was limited by the substrate.
To define the sample universe, we created an inventory using the indirect census technique following Forero ([2002]).
For the stratified sampling method, we define the sampling regions by calculating the aggregated network throughput based on the SINR/MAC throughput mapping previously described.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com