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Andersen, E. B. (1980). Discrete Statistical Models with Social Science Applications. NorthHolland, Amsterdam.Search in Google Scholar
Boer, P., Huisman, M., Snijders, T. and Zeggelink, E.P.H. (2003). StOCNET: an open software system for the advanced statistical analysis of social networks. Version 1.4. Groningen: ProGAMMA / ICS.Search in Google Scholar
Burnham, K. P. and Anderson, D. R. (2002). Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach (2nd ed.). Springer-Verlag, ISBN 0-387-95364-7.Search in Google Scholar
Crossley, N., Bellotti, E., Edwards, G., Everett, M. G., Koskinen, J. and Tranmer, M. (2015) Social Network Analysis, An Actor Centred Approach. Sage Publications Ltd, ISBN: 9781446267769.Search in Google Scholar
Dampster, A.P., Laird, N.M. and Rubin, D.B. (1977). Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society, B (39): 1-38.Search in Google Scholar
Daudin, J. Picard, F. and Robin, S. (2008). A mixture model for random graph. Statistics and computing (18): 173-183.Search in Google Scholar
Hansell, S. (1984). Cooperative groups, weak ties, and the integration of peer friendships. Social Psychology Quarterly, 47, 316-328.10.2307/3033634Search in Google Scholar
Kaiser, M. (2008). Mean clustering coefficients: the role of isolated nodes and leafs on clustering measures for small-world networks. New J. Phys. 10 083042.10.1088/1367-2630/10/8/083042Search in Google Scholar
Kaiser, M. (2008). Mean clustering coefficients: the role of isolated nodes and leafs on clustering measures for small-world networks. New J. Phys. 10 083042.10.1088/1367-2630/10/8/083042Search in Google Scholar
Krackhardt, D. (1987). Cognitive social structures. Social Networks, 9, 104-134.10.1016/0378-8733(87)90009-8Search in Google Scholar
Luce, R.D. and Perry, A.D. (1949). A method of matrix analysis of group structure. Psychometrika 14 (1): 95-116.Search in Google Scholar
Newman, M. (2006). Finding community structure in networks using the eigenvectors of matrices. Phys. Rev. E 74, 036104.10.1103/PhysRevE.74.036104Search in Google Scholar
Newman, M. and Leicht, E. (2007). Mixture models and exploratory analysis in networks. PNAS 104:9564-9569.Search in Google Scholar
Nowicki, K. and Snijders, T. (2001). Estimation and prediction for stochastic blockstructures. J. Amer. Statist. Assoc., 96(455):IO77-IO87.Search in Google Scholar
Snijders, T. and Nowicki, K. (1997). Estimation and prediction for stochastic blockmodels for graphs with latent block structure. Journal of Classification, 14, 75 -100.10.1007/s003579900004Search in Google Scholar
Wasserman, S. and Faust, K. (1994). Social Network Analysis: Methods and Application. Cambridge: Cambridge University Press.10.1017/CBO9780511815478Search in Google Scholar
G. B. Folland. Higher-Order Derivatives and Taylor’s Formula in Several Variables.Search in Google Scholar
Watts, D.J. and Strogatz, S.H. (1998). Collective dynamics of ‘smallworld’ networks. Nature 393 (6684): 440-442.Search in Google Scholar
Yang, Y. (2005). Can the strengths of AIC and BIC be shared?. Biometrika 92: 937-950.Search in Google Scholar
Zachary, W. (1977). An information flow model for conflict and fission in small groups. Journal of Anthropological Research 33, 452-473.10.1086/jar.33.4.3629752Search in Google Scholar