| Name : R-randnet
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| Version : 0.7
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.5.1
| Date : 2024-06-21 07:32:05
|
| Group : Development/Libraries/Other
| Source RPM : R-randnet-0.7-lp153.5.1.src.rpm
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| Size : 0.18 MB
| |
| Packager : (none)
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| Summary : Random Network Model Estimation, Selection and Parameter Tuning
|
Description :
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>). 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 core-periphery 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 DMS-2015298 and DMS-2015134.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
