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The main contribution of this work is to model the correlations of the labels using a directed acyclic graph.
In order to model the correlations among S, B, and T, at least two more random effects need to be introduced into the model to characterize their shared variations.
In this model, the correlations between the baseline and 6-month measurements are taken into account.
We used an autoregressive structure to model the correlations between repeated measures over time.
But correlation network methods can only be applied to model the correlations between numeric variables.
A spatial exponential covariance structure was used to model the correlations between repeated measurements.
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Using the proposed model, the correlation between the antennas was investigated.
For a good fit of model, the correlation coefficient should be at a minimum of 0.80.
Choquet integral [15] is a useful tool to model the correlation or inter-dependence.
A virtual channel is used to model the correlation between the DCT coefficients of the original and SI frames.
Open image in new window Fig. 17 Relation between the BI logs and BI model; the correlation is 94%.
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