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")])
#> Humidity Humidity
#> 71.6 94.8
#> Air.Temp Air.Temp
#> 21.42 28.50
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)
```