Ahmed Mehedi Nizam

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The stochastic Kronecker Graph model can generate large random graph that closely resembles many real world networks. For example, the output graph has a heavy-tailed degree distribution, has a (low) diameter that effectively remains constant over time and obeys the so-called densification power law [1]. Aside from this list of very important graph(More)
Here we calculate the expected number of isolated vertices, edges, self loops and triangles in a random realization of stochastic Kronecker graph. We then establish some bounds on the values of the parameters of the stochastic Kronecker graph which are sufficient to generate large random graph with no isolated vertices, edges, self loops and triangles.(More)
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