R: Growing dot map with information about missing/imputed values

growdotMiss {VIM} | R Documentation

## Growing dot map with information about missing/imputed values

### Description

Map with dots whose sizes correspond to the values in a certain variable. Observations with missing/imputed values in additional variables are highlighted.

### Usage

    growdotMiss(
      x,
      coords,
      map,
      pos = 1,
      delimiter = NULL,
      selection = c("any", "all"),
      log = FALSE,
      col = c("skyblue", "red", "skyblue4", "red4", "orange", "orange4"),
      border = par("bg"),
      alpha = NULL,
      scale = NULL,
      size = NULL,
      exp = c(0, 0.95, 0.05),
      col.map = grey(0.5),
      legend = TRUE,
      legtitle = "Legend",
      cex.legtitle = par("cex"),
      cex.legtext = par("cex"),
      ncircles = 6,
      ndigits = 1,
      interactive = TRUE,
      ...
    )

    ## S3 method for class 'data.frame'
    growdotMiss(
      x,
      coords,
      map,
      pos = 1,
      delimiter = NULL,
      selection = c("any", "all"),
      log = FALSE,
      col = c("skyblue", "red", "skyblue4", "red4", "orange", "orange4"),
      border = par("bg"),
      alpha = NULL,
      scale = NULL,
      size = NULL,
      exp = c(0, 0.95, 0.05),
      col.map = grey(0.5),
      legend = TRUE,
      legtitle = "Legend",
      cex.legtitle = par("cex"),
      cex.legtext = par("cex"),
      ncircles = 6,
      ndigits = 1,
      interactive = TRUE,
      ...
    )

    ## S3 method for class 'survey.design'
    growdotMiss(
      x,
      coords,
      map,
      pos = 1,
      delimiter = NULL,
      selection = c("any", "all"),
      log = FALSE,
      col = c("skyblue", "red", "skyblue4", "red4", "orange", "orange4"),
      border = par("bg"),
      alpha = NULL,
      scale = NULL,
      size = NULL,
      exp = c(0, 0.95, 0.05),
      col.map = grey(0.5),
      legend = TRUE,
      legtitle = "Legend",
      cex.legtitle = par("cex"),
      cex.legtext = par("cex"),
      ncircles = 6,
      ndigits = 1,
      interactive = TRUE,
      ...
    )

    ## Default S3 method:
    growdotMiss(
      x,
      coords,
      map,
      pos = 1,
      delimiter = NULL,
      selection = c("any", "all"),
      log = FALSE,
      col = c("skyblue", "red", "skyblue4", "red4", "orange", "orange4"),
      border = par("bg"),
      alpha = NULL,
      scale = NULL,
      size = NULL,
      exp = c(0, 0.95, 0.05),
      col.map = grey(0.5),
      legend = TRUE,
      legtitle = "Legend",
      cex.legtitle = par("cex"),
      cex.legtext = par("cex"),
      ncircles = 6,
      ndigits = 1,
      interactive = TRUE,
      ...
    )

### Arguments

`x` | a vector, matrix or `data.frame`.
`coords` | a matrix or `data.frame` with two columns giving the spatial coordinates of the observations.
`map` | a background map to be passed to `bgmap`.
`pos` | a numeric value giving the index of the variable determining the dot sizes.
`delimiter` | a character-vector to distinguish between variables and imputation-indices for imputed variables (therefore, `x` needs to have `colnames`). If given, it is used to determine the corresponding imputation-index for any imputed variable (a logical-vector indicating which values of the variable have been imputed). If such imputation-indices are found, they are used for highlighting and the colors are adjusted according to the given colors for imputed variables (see `col`).
`selection` | the selection method for highlighting missing/imputed values in multiple additional variables. Possible values are `"any"` (highlighting of missing/imputed values in any of the additional variables) and `"all"` (highlighting of missing/imputed values in all of the additional variables).
`log` | a logical indicating whether the variable given by `pos` should be log-transformed.
`col` | a vector of length six giving the colors to be used in the plot. If only one color is supplied, it is used for the borders of non-highlighted dots and the surface area of highlighted dots. Else if two colors are supplied, they are recycled.
`border` | a vector of length four giving the colors to be used for the borders of the growing dots. Use `NA` to omit borders.
`alpha` | a numeric value between 0 and 1 giving the level of transparency of the colors, or `NULL`. This can be used to prevent overplotting.
`scale` | scaling factor of the map.
`size` | a vector of length two giving the sizes for the smallest and largest dots.
`exp` | a vector of length three giving the factors that define the shape of the exponential function (see ‘Details’).
`col.map` | the color to be used for the background map.
`legend` | a logical indicating whether a legend should be plotted.
`legtitle` | the title for the legend.
`cex.legtitle` | the character expansion factor to be used for the title of the legend.
`cex.legtext` | the character expansion factor to be used in the legend.
`ncircles` | the number of circles displayed in the legend.
`ndigits` | the number of digits displayed in the legend. Note that \ this is just a suggestion (see `format`).
`interactive` | a logical indicating whether information about certain observations can be displayed interactively (see ‘Details’).
`...` | for `growdotMiss`, further arguments and graphical parameters to be passed to `bgmap`. For `bubbleMiss`, the arguments to be passed to `growdotMiss`.

### Details

The smallest dots correspond to the 10% quantile and the largest dots to the 99% quantile. In between, the dots grow exponentially, with `exp` defining the shape of the exponential function. Missings/imputed missings in the variable of interest will be drawn as rectangles.

If `interactive=TRUE`, detailed information for an observation can be printed on the console by clicking on the corresponding point. Clicking in a region that does not contain any points quits the interactive session.

### Note

The function was renamed to `growdotMiss` in version 1.3. `bubbleMiss` is a (deprecated) wrapper for `growdotMiss` for back compatibility with older versions. However, due to extended functionality, some of the argument positions have changed.

The code is based on (removed from CRAN) bubbleFIN from package StatDA.

### Author(s)

Andreas Alfons, Matthias Templ, Peter Filzmoser, Bernd Prantner

### References

M. Templ, A. Alfons, P. Filzmoser (2012) Exploring incomplete data using visualization tools. Journal of Advances in Data Analysis and Classification, Online first. DOI: 10.1007/s11634-011-0102-y.

### See Also

`bgmap`, `mapMiss`, `colormapMiss`

### Examples

    data(chorizonDL, package = "VIM")
    data(kola.background, package = "VIM")
    coo <- chorizonDL[, c("XCOO", "YCOO")]
    ## for missing values
    x <- chorizonDL[, c("Ca","As", "Bi")]
    growdotMiss(x, coo, kola.background, border = "white")

    ## for imputed values
    x_imp <- kNN(chorizonDL[,c("Ca","As","Bi" )])
    growdotMiss(x_imp, coo, kola.background, delimiter = "_imp", border = "white")

[Package VIM version 5.1.1 Index]