Large deviation principle for the empirical degree measure of preferential attachment random graphs.

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dc.contributor.author Doku-Amponsah, K
dc.contributor.author Mettle, F.O
dc.contributor.author Nortey, E.N.N
dc.date.accessioned 2015-06-23T12:05:39Z
dc.date.accessioned 2017-10-14T12:20:59Z
dc.date.available 2015-06-23T12:05:39Z
dc.date.available 2017-10-14T12:20:59Z
dc.date.issued 2015
dc.identifier.uri http://197.255.68.203/handle/123456789/6251
dc.description.abstract We consider preferential attachment random graphs which may be obtained as follows: It starts with a single node. If a new node appears, it is linked by an edge to one or more existing node(s) with a probability proportional to function of their degree. For a class of linear preferential attachment random graphs we find a large deviation principle (LDP) for the empirical degree measure. In the course of the prove this LDP we establish an LDP for the empirical degree and pair distribution see Theorem 2.3, of the fitness preferential attachment model of random graphs. en_US
dc.publisher International journal of Statistics and Probability en_US
dc.subject Large deviation principle en_US
dc.subject preferential attachment graphs en_US
dc.subject empirical degree measure en_US
dc.subject path empirical en_US
dc.subject degree measure en_US
dc.title Large deviation principle for the empirical degree measure of preferential attachment random graphs. en_US
dc.type Article en_US


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