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 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)