| choosemaxit {clusterMI} | R Documentation |
Diagnostic plot for the number of iterations used in sequential imputation methods
Description
The choosemaxit function plots the within and between variance for each variable (specified in plotvars) against the iteration number for each of the replications (specified in plotm).
Usage
choosemaxit(
output,
plotvars = NULL,
plotm = 1:5,
size = 0.5,
linewidth = 1,
linetype = "dotdash",
xlab = "iterations",
ylab = "var",
title = "Within and between variance plots",
nvar_by_row = 5
)
Arguments
output |
an outpout from the imputedata function |
plotvars |
index of variables for which a curve is plotted |
plotm |
a vector indicating which imputed datasets must be plotted |
size |
size of points |
linewidth |
a numerical value setting the widths of lines |
linetype |
what type of plot should be drawn |
xlab |
a title for the x axis |
ylab |
a title for the y axis |
title |
the main title |
nvar_by_row |
the number of variables that are plotted per window. Default value is 5. |
Value
No return value
Examples
data(wine)
set.seed(123456)
wine.na <- wine
wine.na$cult <- NULL
wine.na <- prodna(wine.na)
nb.clust <- 3 # number of clusters
m <- 3 # number of imputed data sets
maxit <- 50 # number of iterations for FCS imputation
res.imp <- imputedata(data.na = wine.na, method = "FCS-homo",
nb.clust = nb.clust, m = m, maxit = maxit)
choosemaxit(res.imp)
[Package clusterMI version 1.2.1 Index]