We deal with a general preferential attachment graph model with multiple type edges. The types are chosen randomly, in a way that depends on the evolution of the graph. In the N-type case, we define the (generalized) degree of a given vertex as d=(d_1,d_2,…,d_N), where d is the number of type k edges connected to it. We prove the existence of an a.s. asymptotic degree distribution for a general family of preferential attachment random graph models with multi-type edges. More precisely, we show that the proportion of vertices with (generalized) degree d tends to some random variable as the number of steps goes to infinity. We also provide recurrence equations for the asymptotic degree distribution. Finally, we generalize the scale-free prope...
Preferential attachment networks are a type of random network where new nodes are connected to exist...
AbstractA power law degree distribution is established for a graph evolution model based on the grap...
Random graphs is a well-studied field of probability theory, and have proven very useful in a range ...
We deal with a general preferential attachment graph model with multiple type edges. The types are c...
In a 2-parameter scale free model of random graphs it is shown that the asymptotic degree distributi...
In this paper, a random graph process {G(t)}t≥1 is studied and its degree sequence is analyzed. Let ...
In this paper, a random graph process {G(t)} (ta parts per thousand yen1) is studied and its degree ...
In this paper, a random graph process {G(t)}t≥1 is studied and its degree sequence is analyzed. Let ...
We consider the degree distributions of preferential attachment ran-dom graph models with choice sim...
We study preferential attachment models where vertices enter the network with i.i.d. random numbers ...
Preferential attachment is a widely adopted paradigm for understanding the dynamics of social ne...
We consider the preferential attachment model with multiple vertex types introduced by Antunovi ́c,...
PACS 89.75.Fb – Structures and organization in complex systems Abstract – We study the growth of bip...
A random graph evolution mechanism is defined. The evolution studied is a combination of the prefere...
In this paper a random graph evolution rule is defined which can be con- sidered as a generalization...
Preferential attachment networks are a type of random network where new nodes are connected to exist...
AbstractA power law degree distribution is established for a graph evolution model based on the grap...
Random graphs is a well-studied field of probability theory, and have proven very useful in a range ...
We deal with a general preferential attachment graph model with multiple type edges. The types are c...
In a 2-parameter scale free model of random graphs it is shown that the asymptotic degree distributi...
In this paper, a random graph process {G(t)}t≥1 is studied and its degree sequence is analyzed. Let ...
In this paper, a random graph process {G(t)} (ta parts per thousand yen1) is studied and its degree ...
In this paper, a random graph process {G(t)}t≥1 is studied and its degree sequence is analyzed. Let ...
We consider the degree distributions of preferential attachment ran-dom graph models with choice sim...
We study preferential attachment models where vertices enter the network with i.i.d. random numbers ...
Preferential attachment is a widely adopted paradigm for understanding the dynamics of social ne...
We consider the preferential attachment model with multiple vertex types introduced by Antunovi ́c,...
PACS 89.75.Fb – Structures and organization in complex systems Abstract – We study the growth of bip...
A random graph evolution mechanism is defined. The evolution studied is a combination of the prefere...
In this paper a random graph evolution rule is defined which can be con- sidered as a generalization...
Preferential attachment networks are a type of random network where new nodes are connected to exist...
AbstractA power law degree distribution is established for a graph evolution model based on the grap...
Random graphs is a well-studied field of probability theory, and have proven very useful in a range ...