CluMP_view: Cluster profiles' (CluMP results) visualisation
In CluMP: Clustering of Micro Panel Data

Description Usage Arguments Value Examples

View source: R/clump_view.R

This graphical function enables to visualise cluster profiles (mean representatives of each cluster). Available are three types of plots: non-parametric (LOESS method for small/medium or GAM method for complex data of large size. Both methods are applied from ggplot2 representatives (mean within-cluster trajectories) with/without all individual (original) trajectories, and nonparametric mean trajectories with error bars.

CluMP_view(
  CluMPoutput,
  type = "all",
  nb_intervals = NULL,
  return_table = FALSE,
  title = NULL,
  x_title = NULL,
  y_title = NULL,
  plot_NA = FALSE
)

`CluMPoutput`	An object (output) from the `CluMP` function.
`type`	String. Indicates which type of graph is required. Possible values for this argument are: "all" (plots all data with non-parametric mean trajectories), "cont" (only non-parametric mean trajectories) or "breaks" (mean trajectories with error bars).
`nb_intervals`	An integer, positive number (scalar) specifying the number of regular timepoints into which should be follow-up period split. This argument works only with graph type = "breaks". In case of other graph types the argument is ignored. The number of error bars is equal to the number of timepoints specified by this argument.
`return_table`	Logical scalar indicating if the summary table of plotted values in the graph of type = "breaks" should be returned. Default is FALSE.
`title`	String. Optional title for a plot. If undefined, no title will used.
`x_title`	String. An optional title for x axis. If undefined, the variable name after ~ in `formula` will used.
`y_title`	String. An optional title for y axis. If undefined, the variable name before ~ in `formula` will used.
`plot_NA`	Plot NA cluster if exists. Default is FALSE. NA cluster gathers improper individuals (< 3 observations) for longitudinal clustering.

Returns graph for type "all" and "cont" or (list with) graph and table of mean trajectories (if specified) for type = "breaks".

set.seed(123)
dataMale <- GeneratePanel(n = 50, Param = ParamLinear, NbVisit = 10)
dataMale$Gender <- "M"
dataFemale <- GeneratePanel(n = 50, Param = ParamLinear, NbVisit = 10)
dataFemale$ID <- dataFemale$ID + 50
dataFemale$Gender <- "F"
data <- rbind(dataMale, dataFemale)

CluMPoutput <- CluMP(formula = Y ~ Time, group = "ID", data = data, cl_numb = 3)
title <- "Plotting clusters' representatives with error bars"
CluMP_view(CluMPoutput, type = "all" , return_table = TRUE)
CluMP_view(CluMPoutput, type = "cont")
CluMP_view(CluMPoutput, type = "breaks", nb_intervals = 5, return_table=TRUE, title = title)