Plot a per-cluster diagnostic value — PlotClusterDiagnostic • SciDataReportR

Boxplot of any per-participant diagnostic (posterior probability, distance to centroid, outlier score) split by cluster.

Usage

PlotClusterDiagnostic(individual, value, title = NULL, noise_label = 0L)

Arguments

individual: Per-participant diagnostic table containing Cluster.
value: Diagnostic column name.
title: Optional plot title.
noise_label: Cluster value treated as noise, or NULL to disable.

Value

A ggplot object.

Examples

# \donttest{
data(SimulatedPhenotypeData)
df_Training <- dplyr::filter(SimulatedPhenotypeData, .data$Cohort == "Training")
model <- CreateClusterModel_MClust(
  df_Training, paste0("Var", 1:12), method = "finalize",
  final_k = 4, final_model = 1
)
PlotClusterDiagnostic(model$ProbFit$individual, "PosteriorMax")

# }