Estimation of local degree distributions via local weighted averaging and Monte Carlo cross-validation

Paulo Serra (Corresponding author), Michel Mandjes

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Owing to their capability of summarising the interactions between the elements of a system, networks have become a common type of data across a broad range of scientific fields. As networks can be heterogeneous – in the sense that different regions of the network may exhibit different topologies – an important topic concerns the study of their local properties. A method to estimate the local degree distribution of a vertex in a heterogeneous network is developed. The contributions are twofold: firstly, the proposal of an estimator based on local weighted averaging and secondly, the set up of a Monte Carlo cross-validation procedure to pick the parameters of this estimator. The method is illustrated by several numerical experiments, showing in particular that the approach considerably improves upon the natural, empirical estimator.

Original languageEnglish
Article number106886
Number of pages21
JournalComputational Statistics and Data Analysis
Volume144
DOIs
Publication statusPublished - Apr 2020

Fingerprint

Heterogeneous networks
Degree Distribution
Cross-validation
Averaging
Topology
Empirical Estimator
Estimator
Experiments
Local Properties
Heterogeneous Networks
Numerical Experiment
Vertex of a graph
Interaction
Estimate
Range of data

Keywords

  • Local degree distribution
  • Local weighted averaging
  • Monte Carlo cross-validation
  • Oracle inequality
  • Random connection model

Cite this

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Estimation of local degree distributions via local weighted averaging and Monte Carlo cross-validation. / Serra, Paulo (Corresponding author); Mandjes, Michel.

In: Computational Statistics and Data Analysis, Vol. 144, 106886, 04.2020.

Research output: Contribution to journalArticleAcademicpeer-review

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