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, ...)bubbleMiss(...)
data.frame
.data.frame
with two columns giving
the spatial coordinates of the observations.bgmap
.x
needs
to have colnames
). If given, it is used to determine the correspo"any"
(highlighting of missing/imputed values in any of the additional
variables) and pos
should be log-transformed.NA
to omit borders.NULL
. This can be used to
prevent overplotting.format
).growdotMiss
, further arguments and graphical
parameters to be passed to bgmap
. For bubbleMiss
,
the arguments to be passed to growdotMiss
.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.bgmap
, mapMiss
,
colormapMiss
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")
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