TY - JOUR
T1 - Estimation of local degree distributions via local weighted averaging and Monte Carlo cross-validation
AU - Serra, Paulo
AU - Mandjes, Michel
PY - 2020/4
Y1 - 2020/4
N2 - 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.
AB - 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.
KW - Local degree distribution
KW - Local weighted averaging
KW - Monte Carlo cross-validation
KW - Oracle inequality
KW - Random connection model
UR - http://www.scopus.com/inward/record.url?scp=85076260933&partnerID=8YFLogxK
U2 - 10.1016/j.csda.2019.106886
DO - 10.1016/j.csda.2019.106886
M3 - Article
AN - SCOPUS:85076260933
SN - 0167-9473
VL - 144
JO - Computational Statistics and Data Analysis
JF - Computational Statistics and Data Analysis
M1 - 106886
ER -