Stawinoga, Agnieszka (2010) ASSESSMENT OF STOCHASTIC APPROXIMATION METHODS AND OF DEGENERACY DIAGNOSTIC TOOLS IN EXPONENTIAL RANDOM GRAPH MODELS. [Tesi di dottorato] (Inedito)

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Tipologia del documento: Tesi di dottorato
Lingua: English
Titolo: ASSESSMENT OF STOCHASTIC APPROXIMATION METHODS AND OF DEGENERACY DIAGNOSTIC TOOLS IN EXPONENTIAL RANDOM GRAPH MODELS
Autori:
AutoreEmail
Stawinoga, Agnieszkaagnieszka.stawinoga@unina.it
Data: 30 Novembre 2010
Numero di pagine: 148
Istituzione: Università degli Studi di Napoli Federico II
Dipartimento: Matematica e statistica
Scuola di dottorato: Scienze economiche e statistiche
Dottorato: Statistica
Ciclo di dottorato: 23
Coordinatore del Corso di dottorato:
nomeemail
Lauro, Carlo Nataleclauro@unina.it
Tutor:
nomeemail
Giordano, Giuseppeggiordan@unisa.it
Data: 30 Novembre 2010
Numero di pagine: 148
Parole chiave: statistical models for social networks, Exponential Random Graph Models, degeneracy, stochastic approximation methods
Settori scientifico-disciplinari del MIUR: Area 13 - Scienze economiche e statistiche > SECS-S/01 - Statistica
Depositato il: 09 Dic 2010 21:46
Ultima modifica: 05 Dic 2014 14:36
URI: http://www.fedoa.unina.it/id/eprint/8357
DOI: 10.6092/UNINA/FEDOA/8357

Abstract

In recent decades there has been an enormous growth of interest in the notion of social network and the methods of Social Network Analysis (SNA). The methodology developed in the field of network analysis has been categorized into descriptive methods and statistical methods. The statistical methods may be organized into two parts; the first group consists of dyadic and triadic methods which represent statistical models for subgraphs and the second group of statistical models for entire graphs and digraphs. In this work we pay attention to the Exponential Random Graph Models (ERGMs), the statistical models which provide a general framework for modeling dependent data where the dependence can be thought of as a neighborhood effect. The present manuscript is based on two main motivations. Firstly, we are interested to examine model diagnostics and check for degeneracy of ERGMs using different methods and functions. Secondly, we aim to evaluate and compare results obtained for networks of various sizes from three different estimation procedures such as Newton-Raphson, Robbins-Monro and Stepping.

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