Rug representation of missing/imputed values

Source: R/rugNA.R

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

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

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)