Extract the regularization path of a PLNnetwork fit

Usage

coefficient_path(Robject, precision = TRUE, corr = TRUE)

Arguments

Robject: an object with class Networkfamily, i.e. an output from PLNnetwork()
precision: a logical, should the coefficients of the precision matrix Omega or the covariance matrix Sigma be sent back. Default is TRUE.
corr: a logical, should the correlation (partial in case precision = TRUE) be sent back. Default is TRUE.

Value

Sends back a tibble/data.frame.

Examples

data(trichoptera)
trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
fits <- PLNnetwork(Abundance ~ 1, data = trichoptera)
#> 
#>  Initialization...
#>  Adjusting 30 PLN with sparse inverse covariance estimation
#> 	Joint optimization alternating gradient descent and graphical-lasso
#> 	sparsifying penalty = 0.5246191 
	sparsifying penalty = 0.4845754 
	sparsifying penalty = 0.4475881 
	sparsifying penalty = 0.4134241 
	sparsifying penalty = 0.3818678 
	sparsifying penalty = 0.3527202 
	sparsifying penalty = 0.3257973 
	sparsifying penalty = 0.3009295 
	sparsifying penalty = 0.2779598 
	sparsifying penalty = 0.2567434 
	sparsifying penalty = 0.2371464 
	sparsifying penalty = 0.2190452 
	sparsifying penalty = 0.2023257 
	sparsifying penalty = 0.1868823 
	sparsifying penalty = 0.1726178 
	sparsifying penalty = 0.159442 
	sparsifying penalty = 0.1472719 
	sparsifying penalty = 0.1360308 
	sparsifying penalty = 0.1256477 
	sparsifying penalty = 0.1160571 
	sparsifying penalty = 0.1071986 
	sparsifying penalty = 0.09901618 
	sparsifying penalty = 0.09145836 
	sparsifying penalty = 0.08447742 
	sparsifying penalty = 0.07802933 
	sparsifying penalty = 0.07207342 
	sparsifying penalty = 0.06657212 
	sparsifying penalty = 0.06149072 
	sparsifying penalty = 0.05679719 
	sparsifying penalty = 0.05246191 

#>  Post-treatments
#>  DONE!
head(coefficient_path(fits))
#>   Node1 Node2 Coeff   Penalty    Edge
#> 1   Aga   Che     0 0.5246191 Aga|Che
#> 2   Ath   Che     0 0.5246191 Ath|Che
#> 3   Cea   Che     0 0.5246191 Cea|Che
#> 4   Ced   Che     0 0.5246191 Ced|Che
#> 5   All   Che     0 0.5246191 All|Che
#> 6   Che   Hyc     0 0.5246191 Che|Hyc