Stochastic block model: Difference between revisions

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m Dissortative is a mispelling of disassortative https://en.wiktionary.org/wiki/dissortative
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If the probability matrix is a constant, in the sense that <math>P_{ij} = p</math> for all <math>i,j</math>, then the result is the [[Erdős–Rényi model]] <math>G(n,p)</math>. This case is degenerate—the partition into communities becomes irrelevant—but it illustrates a close relationship to the Erdős–Rényi model.
 
The ''planted partition model'' is the special case that the values of the probability matrix <math>P</math> are a constant <math>p</math> on the diagonal and another constant <math>q</math> off the diagonal. Thus two vertices within the same community share an edge with probability <math>p</math>, while two vertices in different communities share an edge with probability <math>q</math>. Sometimes it is this restricted model that is called the stochastic block model. The case where <math>p > q</math> is called an ''assortative'' model, while the case <math>p < q</math> is called ''dissortativedisassortative''.
 
Returning to the general stochastic block model, a model is called ''strongly assortative'' if <math>P_{ii} > P_{jk}</math> whenever <math>j \neq k</math>: all diagonal entries dominate all off-diagonal entries. A model is called ''weakly assortative'' if <math>P_{ii} > P_{ij}</math> whenever <math>i \neq j</math>: each diagonal entry is only required to dominate the rest of its own row and column.<ref name="al14" /> ''DissortativeDisassortative'' forms of this terminology exist, by reversing all inequalities. Algorithmic recovery is often easier against block models with assortative or dissortativedisassortative conditions of this form.<ref name="al14" />
 
== Typical statistical tasks ==