ASSESSMENT OF STOCHASTIC APPROXIMATION METHODS AND OF DEGENERACY DIAGNOSTIC TOOLS IN EXPONENTIAL RANDOM GRAPH MODELS

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

Full text disponibile come:

[img]
Preview
PDF - Richiede un editor Pdf del tipo GSview, Xpdf o Adobe Acrobat Reader
3206Kb

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.

Tipologia di documento:Tesi di dottorato
Parole chiave:statistical models for social networks, Exponential Random Graph Models, degeneracy, stochastic approximation methods
Settori scientifico-disciplinari MIUR:Area 13 Scienze economiche e statistiche > SECS-S/01 STATISTICA
Coordinatori della Scuola di dottorato:
Coordinatore del Corso di dottoratoe-mail (se nota)
Lauro, Carloclauro@unina.it
Tutor della Scuola di dottorato:
Tutor del Corso di dottoratoe-mail (se nota)
Giordano, Giuseppeggiordan@unisa.it
Stato del full text:Accessibile
Data:30 Novembre 2010
Numero di pagine:148
Istituzione:Università  degli Studi di Napoli Federico II
Dipartimento o Struttura:Matematica e statistica
Tipo di tesi:Dottorato
Stato dell'Eprint:Inedito
Scuola di dottorato:Scienze economiche e statistiche
Denominazione del dottorato:Statistica
Ciclo di dottorato:23
Numero di sistema:8357
Depositato il:09 Dicembre 2010 22:46
Ultima modifica:01 Settembre 2011 09:38

Solo per gli Amministratori dell'archivio: edita il record