A Sequential Importance Sampling Algorithm for Generating Random Graphs with Prescribed Degrees
نویسندگان
چکیده
Random graphs with a given degree sequence are a useful model capturing several features absent in the classical Erdős-Rényi model, such as dependent edges and non-binomial degrees. In this paper, we use a characterization due to Erdős and Gallai to develop a sequential algorithm for generating a random labeled graph with a given degree sequence. The algorithm is easy to implement and allows surprisingly efficient sequential importance sampling. Applications are given, including simulating a biological network and estimating the number of graphs with a given degree sequence.
منابع مشابه
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ورودعنوان ژورنال:
- Internet Mathematics
دوره 6 شماره
صفحات -
تاریخ انتشار 2011