randnet: Random Network Model Selection and Parameter Tuning

Model selection and parameter tuning procedures for a class of random network models. The model selection can be done by a general cross-validation framework called ECV from Li et. al. (2016) <arXiv:1612.04717> . Several other model-based and task-specific methods are also included, such as NCV from Chen and Lei (2016) <arXiv:1411.1715>, likelihood ratio method from Wang and Bickel (2015) <arXiv:1502.02069>, spectral methods from Le and Levina (2015) <arXiv:1507.00827>. Many network analysis methods are also implemented, such as the regularized spectral clustering (Amini et. al. 2013 <doi:10.1214/13-AOS1138>) and its degree corrected version and graphon neighborhood smoothing (Zhang et. al. 2015 <arXiv:1509.08588>).

Package details

AuthorTianxi Li, Elizaveta Levina, Ji Zhu
MaintainerTianxi Li <[email protected]>
LicenseGPL (>= 2)
Version0.2
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("randnet")

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randnet documentation built on May 1, 2019, 10:18 p.m.