Plot MrSGUIDE regression tree

Source: R/plot.R

Plot MrSGUIDE regression tree

plotTree(
  mrsobj,
  digits = 3,
  height = "600px",
  width = "100%",
  nodefontSize = 16,
  edgefontSize = 14,
  minNodeSize = 15,
  maxNodeSize = 30,
  nodeFixed = FALSE,
  edgeColor = "#8181F7",
  highlightNearest = list(enabled = TRUE, degree = list(from = 50000, to = 0), hover =
    FALSE, algorithm = "hierarchical"),
  collapse = list(enabled = FALSE, fit = TRUE, resetHighlight = TRUE, clusterOptions =
    list(fixed = TRUE, physics = FALSE)),
  alphaInd = 3
)

Arguments

mrsobj

MrSGUIDE object
digits

digits for split threshold
height

figure height
width

figure width
nodefontSize

node font size
edgefontSize

edge font size
minNodeSize

minimal node size
maxNodeSize

maximum node size
nodeFixed

whether you can drag node
edgeColor

edge color
highlightNearest

choose node will highlight nearby
collapse

list, collapse or not using double click on a node
alphaInd

1 is original alpha, 2 is individual level alpha, 3 is overall alpha

Value

A list contains plot figure

treeplot

The tree plot uses visNetwork function.

nodeTreat

A data frame contain each elements used for tree plot.

trtPlot

A treatment effects plot of each node.

Examples

library(MrSGUIDE)
set.seed(1234)

N = 200
np = 3

numX <- matrix(rnorm(N * np), N, np) ## numerical features
gender <- sample(c('Male', 'Female'), N, replace = TRUE)
country <- sample(c('US', 'UK', 'China', 'Japan'), N, replace = TRUE)

z <- sample(c(0, 1), N, replace = TRUE) # Binary treatment assignment

y1 <- numX[, 1] + 1 * z * (gender == 'Female') + rnorm(N)
y2 <- numX[, 2] + 2 * z * (gender == 'Female') + rnorm(N)

train <- data.frame(numX, gender, country, z, y1, y2)
role <- c(rep('n', 3), 'c', 'c', 'r', 'd', 'd')

mrsobj <- MrSFit(dataframe = train, role = role)
plotObj <- plotTree(mrsobj)
#plotObj$treePlot
plotObj$nodeTreat ## node information
#>      Estimate       SE Assignment Outcome Node    Quantity       ymin      ymax
#> 2    0.995726 0.189337        z.1      y1    2 Node: 2; y1  0.6246255 1.3668265
#> 21   2.062110 0.180745        z.1      y2    2 Node: 2; y2  1.7078498 2.4163702
#> 22  -0.227258 0.200356        z.1      y1    3 Node: 3; y1 -0.6199558 0.1654398
#> 211 -0.036876 0.208765        z.1      y2    3 Node: 3; y2 -0.4460554 0.3723034
#>     zalpha
#> 2     1.96
#> 21    1.96
#> 22    1.96
#> 211   1.96
plotObj$trtPlot ## treatment effect plot