Markov graphs
O Frank, D Strauss - Journal of the american Statistical association, 1986 - Taylor & Francis
O Frank, D Strauss
Journal of the american Statistical association, 1986•Taylor & FrancisLog-linear statistical models are used to characterize random graphs with general
dependence structure and with Markov dependence. Sufficient statistics for Markov graphs
are shown to be given by counts of various triangles and stars. In particular, we show under
which assumptions the triad counts are sufficient statistics. We discuss inference
methodology for some simple Markov graphs.
dependence structure and with Markov dependence. Sufficient statistics for Markov graphs
are shown to be given by counts of various triangles and stars. In particular, we show under
which assumptions the triad counts are sufficient statistics. We discuss inference
methodology for some simple Markov graphs.
Abstract
Log-linear statistical models are used to characterize random graphs with general dependence structure and with Markov dependence. Sufficient statistics for Markov graphs are shown to be given by counts of various triangles and stars. In particular, we show under which assumptions the triad counts are sufficient statistics. We discuss inference methodology for some simple Markov graphs.
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