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]