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 [Tesi di dottorato] (Unpublished)

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Item Type:	Tesi di dottorato
Lingua:	English
Title:	ASSESSMENT OF STOCHASTIC APPROXIMATION METHODS AND OF DEGENERACY DIAGNOSTIC TOOLS IN EXPONENTIAL RANDOM GRAPH MODELS
Creators:	Creators Email Stawinoga, Agnieszka agnieszka.stawinoga@unina.it
Date:	30 November 2010
Number of Pages:	148
Institution:	Università degli Studi di Napoli Federico II
Department:	Matematica e statistica
Scuola di dottorato:	Scienze economiche e statistiche
Dottorato:	Statistica
Ciclo di dottorato:	23
Coordinatore del Corso di dottorato:	nome email Lauro, Carlo Natale clauro@unina.it
Tutor:	nome email Giordano, Giuseppe ggiordan@unisa.it
Date:	30 November 2010
Number of Pages:	148
Uncontrolled Keywords:	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
Date Deposited:	09 Dec 2010 21:46
Last Modified:	05 Dec 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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