Open AccessDegree Distributions in Sexual Networks: A Framework for Evaluating Evidence
Author(s) -
Deven T. Hamilton,
Mark S. Handcock,
Martina Morris
Publication year - 2008
Publication title -
sexually transmitted diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.507
H-Index - 105
eISSN - 1537-4521
pISSN - 0148-5717
DOI - 10.1097/olq.0b013e3181453a84
Subject(s) - akaike information criterion , goodness of fit , bayesian information criterion , econometrics , degree distribution , bayesian probability , deviance information criterion , statistics , computer science , bayesian inference , mathematics , complex network , world wide web
We present a likelihood based statistical framework to test the fit of power-law and alternative social process models for the degree distribution, and derive the sexually transmitted infection epidemic predictions from each model.