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On the other hand, supposing that the data for all three metabolites, A, B, and C, are available and the data show that A and C increasing whereas B decreasing.
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We suppose that the data are scattered and less uniform.
Suppose that the data bit is discrete uniform distribution in '0' and '1'.
We have supposed that the data used for the test are the ones relative to the characteristics of the network LTE.
A more structural view of how fluctuations around trend-growth are determined is to suppose that the data are generated by a mixture process.
We suppose that the data obtained in the present study can contribute to understanding of neurophysiological processes underlying the comorbidity of OFP and headache.
Suppose that the data (image patch) x ∈ R m admits a sparse approximation over an over-complete dictionary Φ ∈ R n×m (K > m) with K atoms.
Suppose that the data consist of n independent observations x i =min(X i,C i ) and δ i =I(X i ≤C i ) is such that δ i =1 if X i is a time to event and δ i =0 if it is right censored for i=1,…,n.
Suppose that the data set has n observations with p genes.
Suppose that the data we are interested in, x i, x 2, …, x n, do not possess a natural order.
Suppose that the data (T i, Δ i, X i, Z i ) are available for an individual i = 1,..., n.
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