PLNnetworkfamily or ZIPLNnetworkfamily)R/PLNnetworkfamily-S3methods.R
plot.Networkfamily.RdDisplay various outputs (goodness-of-fit criteria, robustness, diagnostic) associated with a collection of network fits (either PLNnetworkfamily or ZIPLNnetworkfamily)
# S3 method for class 'Networkfamily'
plot(
x,
type = c("criteria", "stability", "diagnostic"),
criteria = c("loglik", "pen_loglik", "BIC", "EBIC"),
reverse = FALSE,
log.x = TRUE,
stability = 0.9,
...
)
# S3 method for class 'PLNnetworkfamily'
plot(
x,
type = c("criteria", "stability", "diagnostic"),
criteria = c("loglik", "pen_loglik", "BIC", "EBIC"),
reverse = FALSE,
log.x = TRUE,
stability = 0.9,
...
)
# S3 method for class 'ZIPLNnetworkfamily'
plot(
x,
type = c("criteria", "stability", "diagnostic"),
criteria = c("loglik", "pen_loglik", "BIC", "EBIC"),
reverse = FALSE,
log.x = TRUE,
stability = 0.9,
...
)an R6 object with class PLNnetworkfamily or ZIPLNnetworkfamily
a character, either "criteria", "stability" or "diagnostic" for the type of plot.
Vector of criteria to plot, to be selected among "loglik" (log-likelihood),
"BIC", "ICL", "R_squared", "EBIC" and "pen_loglik" (penalized log-likelihood).
Default is c("loglik", "pen_loglik", "BIC", "EBIC"). Only used when type = "criteria".
A logical indicating whether to plot the value of the criteria in the "natural" direction (loglik - 0.5 penalty) or in the "reverse" direction (-2 loglik + penalty). Default to FALSE, i.e use the natural direction, on the same scale as the log-likelihood.
logical: should the x-axis be represented in log-scale? Default is TRUE.
scalar: the targeted level of stability in stability plot. Default is .9.
additional parameters for S3 compatibility. Not used
Produces either a diagnostic plot (with type = 'diagnostic'), a stability plot
(with type = 'stability') or the evolution of the criteria of the different models considered
(with type = 'criteria', the default).
The BIC and ICL criteria have the form 'loglik - 1/2 * penalty'
so that they are on the same scale as the model log-likelihood. You can change this direction and use the alternate form '-2*loglik + penalty', as some authors do, by setting reverse = TRUE.
plot(PLNnetworkfamily): Display various outputs associated with a collection of network fits
plot(ZIPLNnetworkfamily): Display various outputs associated with a collection of network fits
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 = 7.264447
sparsifying penalty = 6.709958
sparsifying penalty = 6.197792
sparsifying penalty = 5.72472
sparsifying penalty = 5.287757
sparsifying penalty = 4.884147
sparsifying penalty = 4.511344
sparsifying penalty = 4.166997
sparsifying penalty = 3.848934
sparsifying penalty = 3.555148
sparsifying penalty = 3.283787
sparsifying penalty = 3.033138
sparsifying penalty = 2.801621
sparsifying penalty = 2.587776
sparsifying penalty = 2.390253
sparsifying penalty = 2.207807
sparsifying penalty = 2.039287
sparsifying penalty = 1.88363
sparsifying penalty = 1.739854
sparsifying penalty = 1.607053
sparsifying penalty = 1.484388
sparsifying penalty = 1.371086
sparsifying penalty = 1.266432
sparsifying penalty = 1.169766
sparsifying penalty = 1.080479
sparsifying penalty = 0.998007
sparsifying penalty = 0.9218299
sparsifying penalty = 0.8514675
sparsifying penalty = 0.7864757
sparsifying penalty = 0.7264447
#> Post-treatments
#> DONE!
if (FALSE) { # \dontrun{
plot(fits)
} # }