doc: Replace package with reference link

R/SMD_example_data.R

@@ -5,8 +5,8 @@
 #' with constant effect sizes of 1 and X7 to X9 are noncausal with effect size of 0. The outcome y is a linear combination of the causal
 #' predictor variables and a normally distributed error term. All basic variables were sampled from a normal distribution
 #' (N(0,1)) just like the noise (N(0,0.2)). For each of the six basic variables X1, X2, X3, X7, X8, and X9 ten variables
-#' with predefined correlations of 0.9 for X1 and X7, 0.6 for X2 and X8, and 0.3 for X3 and X9 were obtained by [WGCNA::simulateModule()] of
-#' the R package WGCNA. The ten variables of each basis variable are labeled: Cp_basicvariable_number. Additional non-correlated and
+#' with predefined correlations of 0.9 for X1 and X7, 0.6 for X2 and X8, and 0.3 for X3 and X9 were obtained by `simulateModule()` of
+#' the R package [WGCNA](https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-9-559). The ten variables of each basis variable are labeled: Cp_basicvariable_number. Additional non-correlated and
 #' independent predictor variables (cgn) were simulated using the standard normal distribution to reach a total number of 200 variables.
 #'
 #' @docType data

man/SMD_example_data.Rd

@@ -16,8 +16,8 @@ For the simulation of the 200 additional variables nine variables X1,…,X9 call
 with constant effect sizes of 1 and X7 to X9 are noncausal with effect size of 0. The outcome y is a linear combination of the causal
 predictor variables and a normally distributed error term. All basic variables were sampled from a normal distribution
 (N(0,1)) just like the noise (N(0,0.2)). For each of the six basic variables X1, X2, X3, X7, X8, and X9 ten variables
-with predefined correlations of 0.9 for X1 and X7, 0.6 for X2 and X8, and 0.3 for X3 and X9 were obtained by \code{\link[WGCNA:simulateModule]{WGCNA::simulateModule()}} of
-the R package WGCNA. The ten variables of each basis variable are labeled: Cp_basicvariable_number. Additional non-correlated and
+with predefined correlations of 0.9 for X1 and X7, 0.6 for X2 and X8, and 0.3 for X3 and X9 were obtained by \code{simulateModule()} of
+the R package \href{https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-9-559}{WGCNA}. The ten variables of each basis variable are labeled: Cp_basicvariable_number. Additional non-correlated and
 independent predictor variables (cgn) were simulated using the standard normal distribution to reach a total number of 200 variables.
 }
 \keyword{datasets}