rugNA: Rug representation of missing/imputed values

In VIM: Visualization and Imputation of Missing Values

Rug representation of missing/imputed values

Description

Add a rug representation of missing/imputed values in only one of the variables to scatterplots.

Usage

rugNA(
  x,
  y,
  ticksize = NULL,
  side = 1,
  col = "red",
  alpha = NULL,
  miss = NULL,
  lwd = 0.5,
  ...
)

Arguments

x, y	numeric vectors.
ticksize	the length of the ticks. Positive lengths give inward ticks.
side	an integer giving the side of the plot to draw the rug representation.
col	the color to be used for the ticks.
alpha	the alpha value (between 0 and 1).
miss	a data.frame or matrix with two columns and logical values. If NULL, x and y are searched for missing values, otherwise, the first column of miss is used to determine the imputed values in x and the second one for the imputed values in y.
lwd	the line width to be used for the ticks.
...	further arguments to be passed to graphics::Axis().

Details

If side is 1 or 3, the rug representation consists of values available in x but missing/imputed in y. Else if side is 2 or 4, it consists of values available in y but missing/imputed in x.

Author(s)

Andreas Alfons, modifications by Bernd Prantner

Examples

data(tao, package = "VIM")
## for missing values
x <- tao[, "Air.Temp"]
y <- tao[, "Humidity"]
plot(x, y)
rugNA(x, y, side = 1)
rugNA(x, y, side = 2)

## for imputed values
x_imp <- kNN(tao[, c("Air.Temp","Humidity")])
x <- x_imp[, "Air.Temp"]
y <- x_imp[, "Humidity"]
miss <- x_imp[, c("Air.Temp_imp","Humidity_imp")]
plot(x, y)
rugNA(x, y, side = 1, col = "orange", miss = miss)
rugNA(x, y, side = 2, col = "orange", miss = miss)

VIM documentation built on Aug. 25, 2022, 5:07 p.m.