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In the next subsection we discuss methods to obtain confidence intervals using random effects logistic model for the setting of clustered data.
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Dictionaries are designed for a set of clustered data.
The properties of the best set of clustered data are then utilized to develop the respective FCs.
We applied the algorithm over the training set to produce a set of clustered sub-cavities.
More than 40 complete sets of clusters, using different parameter settings, were generated and stored.
The two data structures are designed to find the matching sub-clusters between different clusterings and to obtain the final set of clusters through a coherent merging process.
An interesting and sometimes surprising set of clusters appear".
"Disappointingly, we found no difference in the number of new infections between these two randomised sets of clusters," says Deenan Pillay, director of the Africa Centre and professor of virology at University College London.
return Set of clusters.
Denote the set of clusters as S={S1,S2,…,S ι }.
These two parameters are included in the set of cluster parameters, being cluster selection parameters.
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