Description Usage Arguments Examples
The function plot.treemox
allows to display binary
trees of PATHMOX and TECHMOX analyses. If
shadow.size=0
, no shadows are drawn.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | ## S3 method for class 'treemox'
plot(x, root.col = "#eeeeee",
root.bor = "#cccccc", root.txt = "#757575",
root.cex = 0.8, root.lwd = 3, root.shadow = "gray40",
node.col = "#feb769", node.bor = "#FE9929",
node.txt = "#555555", node.cex = 0.7, node.lwd = 3,
node.shadow = "gray30", leaf.col = "#93c4e5",
leaf.bor = "#5a99c5", leaf.txt = "#555555",
leaf.cex = 0.7, leaf.lwd = 3, leaf.shadow = "gray30",
shadow.size = 0, arr.lwd = 3, lcol = "#ddddddbb",
arr.col = "gray95", seg.cex = 0.7, seg.col = "#2cb0a7",
cat.cex = 0.8, cat.col = "#555555", show.pval = TRUE,
pval.col = "#2cb0a7", main = NULL, cex.main = 1,
col.main = "gray50", ...)
|
x |
An object of class |
root.col |
Fill color of root node. |
root.bor |
Border color of root node. |
root.txt |
Text color of root node. |
root.cex |
magnification to be used for text in root node. |
root.lwd |
Line width of border in the root node. |
root.shadow |
Color of shadow of root node. |
node.col |
Fill color of child nodes. |
node.bor |
Border color of child nodes. |
node.txt |
Text color of child nodes. |
node.cex |
magnification to be used for text in child nodes. |
node.lwd |
Line width of border in child nodes. |
node.shadow |
Color of shadow of child nodes. |
leaf.col |
Fill color of leaf nodes. |
leaf.bor |
Border color of leaf nodes. |
leaf.txt |
Text color of leaf nodes. |
leaf.cex |
magnification to be used for text in leaf nodes. |
leaf.lwd |
Line width of border in leaf nodes. |
leaf.shadow |
Color of shadow of leaf nodes. |
shadow.size |
Relative size of shadows. |
arr.lwd |
Line width of the tree branches. |
lcol |
color of lines |
arr.col |
color of arrows |
seg.cex |
A numerical value indicating the magnification to be used for plotting text. |
seg.col |
The color to be used for the labels of the segmentation variables. |
cat.cex |
magnification to be used for the categories |
cat.col |
The color to be used for the labels of the categories |
show.pval |
Logical value indicating whether the p-values should be plotted. |
pval.col |
The color to be used for the labels of the p-values. |
main |
A main title for the plot. |
cex.main |
The magnification to be used for the main title. |
col.main |
Color to be used for the main title |
... |
Further arguments are ignored. |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | ## Not run:
## example of PLS-PM in customer satisfaction analysis
## model with seven LVs and reflective indicators
data(csimobile)
# select manifest variables
data_mobile = csimobile[,8:33]
# define path matrix (inner model)
IMAG = c(0, 0, 0, 0, 0, 0, 0)
EXPE = c(1, 0, 0, 0, 0, 0, 0)
QUAL = c(0, 1, 0, 0, 0, 0, 0)
VAL = c(0, 1, 1, 0, 0, 0, 0)
SAT = c(1, 1, 1, 1, 0, 0, 0)
COM = c(0, 0, 0, 0, 1, 0, 0)
LOY = c(1, 0, 0, 0, 1, 1, 0)
mob_path = rbind(IMAG, EXPE, QUAL, VAL, SAT, COM, LOY)
# blocks of indicators (outer model)
mob_outer = list(1:5, 6:9, 10:15, 16:18, 19:21, 22:24, 25:26)
mob_modes = rep("A", 7)
# apply plspm
mob_pls = plspm(data_mobile, mob_path, mob_blocks, modes = mob_modes,
scheme = "factor", scaled = FALSE)
# re-ordering those segmentation variables with ordinal scale
# (Age and Education)
csimobile$Education = factor(csimobile$Education,
levels=c("basic","highschool","university"),
ordered=TRUE)
# select the segmentation variables
seg_vars = csimobile[,1:7]
# Pathmox Analysis
mob_pathmox = pathmox(mob_pls, seg_vars, signif=.10, size=.10, deep=2)
# plot pathmox tree
plot(mob_pathmox, root.col="lightblue", node.col="turquoise", leaf.col="skyblue3",
shadow.size=0, seg.col="blue2", pval.col="magenta")
## End(Not run)
|
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