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nicholasjclark
MRFcov:Markov Random Fields with Additional Covariates
Approximate node interaction parameters of Markov Random Fields graphical networks. Models can incorporate additional covariates, allowing users to estimate how interactions between nodes in the graph are predicted to change across covariate gradients. The general methods implemented in this package are described in Clark et al. (2018) <doi:10.1002/ecy.2221>.
Maintained by Nicholas J Clark. Last updated 1 years ago.
conditional-random-fieldsgraphical-modelsmachine-learningmarkov-random-fieldmultivariate-analysismultivariate-statisticsnetwork-analysisnetworks
24 stars 6.03 score 30 scripts