regenerating doc

NAMESPACE

@@ -20,8 +20,10 @@ S3method(plot,PLNPCAfit)
 S3method(plot,PLNfamily)
 S3method(plot,PLNmixturefamily)
 S3method(plot,PLNmixturefit)
+S3method(plot,PLNnetworkfamily)
 S3method(plot,PLNnetworkfit)
 S3method(plot,ZIPLNfit_sparse)
+S3method(plot,ZIPLNnetworkfamily)
 S3method(predict,PLNLDAfit)
 S3method(predict,PLNfit)
 S3method(predict,PLNmixturefit)

R/PLNnetworkfamily-S3methods.R

@@ -8,7 +8,7 @@
 ## Auxiliary functions to check the given class of an objet
 isPLNnetworkfamily <- function(Robject) {inherits(Robject, "Networkfamily")}
 
-#' Display various outputs (goodness-of-fit criteria, robustness, diagnostic) associated with a collection of PLNnetwork fits (a [`PLNnetworkfamily`])
+#' Display various outputs (goodness-of-fit criteria, robustness, diagnostic) associated with a collection of network fits (either [`PLNnetworkfamily`] or [`ZIPLNnetworkfamily`])
 #'
 #' @inheritParams plot.PLNfamily
 #' @inherit plot.PLNfamily return details
@@ -20,7 +20,6 @@ isPLNnetworkfamily <- function(Robject) {inherits(Robject, "Networkfamily")}
 #' @param log.x logical: should the x-axis be represented in log-scale? Default is `TRUE`.
 #' @param stability scalar: the targeted level of stability in stability plot. Default is .9.
 #'
-#'
 #' @examples
 #' data(trichoptera)
 #' trichoptera <- prepare_data(trichoptera$Abundance, trichoptera$Covariate)
@@ -32,8 +31,7 @@ isPLNnetworkfamily <- function(Robject) {inherits(Robject, "Networkfamily")}
 #' (with \code{type = 'stability'}) or the evolution of the criteria of the different models considered
 #' (with \code{type = 'criteria'}, the default).
 #' @export
-plot.Networkfamily <-
-  function(x,
+plot.Networkfamily <- function(x,
            type     = c("criteria", "stability", "diagnostic"),
            criteria = c("loglik", "pen_loglik", "BIC", "EBIC"),
            reverse = FALSE,
@@ -51,6 +49,14 @@ plot.Networkfamily <-
   p
 }
 
+#' @describeIn plot.Networkfamily Display various outputs associated with a collection of network fits
+#' @export
+plot.PLNnetworkfamily <- plot.Networkfamily
+
+#' @describeIn plot.Networkfamily Display various outputs associated with a collection of network fits
+#' @export
+plot.ZIPLNnetworkfamily <- plot.Networkfamily
+
 #' @describeIn getModel Model extraction for [`PLNnetworkfamily`]
 #' @export
 getModel.Networkfamily <- function(Robject, var, index = NULL) {

R/PLNnetworkfamily-class.R

@@ -494,14 +494,15 @@ ZIPLNnetworkfamily <- R6Class(
         control$trace <- 0
         control$config_optim$trace <- 0
 
-        myPLN <- PLNnetworkfamily$new(penalties  = self$penalties,
-                                      responses  = self$responses [subsample, , drop = FALSE],
-                                      covariates = self$covariates[subsample, , drop = FALSE],
-                                      offsets    = self$offsets   [subsample, , drop = FALSE],
-                                      formula    = private$formula,
-                                      weights    = self$weights   [subsample], control = control)
-
-        myPLN$optimize(control$config_optim)
+        data <- list(
+          Y  = self$responses [subsample, , drop = FALSE],
+          X = self$covariates[subsample, , drop = FALSE],
+          O = self$offsets   [subsample, , drop = FALSE],
+          w = self$weights   [subsample], formula    = private$formula)
+
+        myPLN <- ZIPLNnetworkfamily$new(self$penalties, data, control)
+        myPLN$optimize(data, control$config_optim)
+
         nets <- do.call(cbind, lapply(myPLN$models, function(model) {
           as.matrix(model$latent_network("support"))[upper.tri(diag(private$p))]
         }))

R/ZIPLNfit-class.R

@@ -75,7 +75,7 @@ ZIPLNfit <- R6Class(
       private$X0      <- data$X0
       ## initialize the covariance model
       private$covariance <- control$covariance
-      private$ziparam <- control$ziparam
+      private$ziparam    <- control$ziparam
 
       if (isZIPLNfit(control$inception)) {
         private$R  <- control$inception$var_par$R