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In another perspective, the SATBM directly models the correlations between the dimensions in the observed features while the ARBM does not.
Ignoring the Poly models, the correlations between predictions from the different models were generally high (>0.9) for line W1.
For grouped data models, the correlations were over 0.98 for CON and 0.96 for FAT scores between EBV from TlogLWM and GDM.
For threshold linear models, the correlations were over 0.98 for CON and 0.95 for FAT scores between EBV from TLM and SEXTLM, much higher than the results of Varona et al. [ 5].
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For all of the selected models, the correlation coefficient reached the high values of 0.972 0.981.
The PCC-SSLPP method models the correlation information between two images in the graph construction step of SSLPP.
The system uses a coefficient level noise model [23] which models the correlation noise for a single coefficient of a subband of a hypothesis as being Laplace distributed.
In[45], a new correlation model for the temporal and inter-view side information is proposed: the smaller the difference between the two SIs, the smaller is the variance of the probability density function (PDF) that models the correlation noise.
For complex models, the correlation equations (Eqs. (10), (14), (16)) cannot be analytically expressed.
For both models, the correlation structure was selected based on the model fit, measured by the quasi-likelihood under the independence model criterion [ 23].
The mixed model includes a random litter effect, which models the correlation between pups within a litter and allows the pup to be the unit of analysis.
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Justyna Jupowicz-Kozak
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