Goodness of fit tests for random multigraph models

Autor: Termeh Shafie
Rok vydání: 2022
Předmět:
Statistics and Probability
soziales Netzwerk
Modell
Sociology & anthropology
Aggregation
Allgemeine Soziologie
Makrosoziologie
spezielle Theorien und Schulen
Entwicklung und Geschichte der Soziologie
Statistik
statistical test
General Sociology
Basic Research
General Concepts and History of Sociology
Sociological Theories
Social sciences
sociology
anthropology
Network model
multivariate networks
data aggregation
random multigraphs
goodness of fit
random stub matching
Erhebungstechniken und Analysetechniken der Sozialwissenschaften
Sozialwissenschaften
Soziologie
model
statistischer Test
Daten
Netzwerk
Methods and Techniques of Data Collection and Data Analysis
Statistical Methods
Computer Methods
data
Soziologie
Anthropologie
statistics
network
ddc:300
social network
Statistics
Probability and Uncertainty
ddc:301
Zdroj: Journal of Applied Statistics
DOI: 10.6084/m9.figshare.20351387.v1
Popis: Goodness of fit tests for two probabilistic multigraph models are presented. The first model is random stub matching given fixed degrees (RSM) so that edge assignments to vertex pair sites are dependent, and the second is independent edge assignments (IEA) according to a common probability distribution. Tests are performed using goodness of fit measures between the edge multiplicity sequence of an observed multigraph, and the expected one according to a simple or composite hypothesis. Test statistics of Pearson type and of likelihood ratio type are used, and the expected values of the Pearson statistic under the different models are derived. Test performances based on simulations indicate that even for small number of edges, the null distributions of both statistics are well approximated by their asymptotic χ2-distribution. The non-null distributions of the test statistics can be well approximated by proposed adjusted χ2-distributions used for power approximations. The influence of RSM on both test statistics is substantial for small number of edges and implies a shift of their distributions towards smaller values compared to what holds true for the null distributions under IEA. Two applications on social networks are included to illustrate how the tests can guide in the analysis of social structure.
Databáze: OpenAIRE
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