Model selection and parameter tuning procedures for a class of random network models. The model selection can be done by a general crossvalidation framework called ECV from Li et. al. (2016) <arXiv:1612.04717> . Several other modelbased and taskspecific 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:10.1214/13AOS1138>) and its degree corrected version and graphon neighborhood smoothing (Zhang et. al. 2015 <arXiv:1509.08588>). It also includes the consensus clustering of Gao et. al. (2014) <arXiv:1410.5837>, the method of moments estimation of nomination SBM of Li et. al. (2020) <arxiv:2008.03652>, and the network mixing method of Li and Le (2021) <arxiv:2106.02803>. It also includes the informative coreperiphery data processing method of Miao and Li (2021) <arXiv:2101.06388>. The work to build and improve this package is partially supported by the NSF grants DMS2015298 and DMS2015134.
Package details 


Author  Tianxi Li [aut, cre], Elizeveta Levina [aut], Ji Zhu [aut], Can M. Le [aut] 
Maintainer  Tianxi Li <tianxili@virginia.edu> 
License  GPL (>= 2) 
Version  0.7 
Package repository  View on CRAN 
Installation 
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