Description Usage Arguments Details Note Author(s) See Also Examples
Display one or more binary variables by using black bars for presence/validity of a condition, empty space for absence/invalidity, and an extra color for missing values. Additionally, an index plot for one interval scaled variable can be added, possibly with a smoothing function (OLD version, to be deprecated).
1 2 3 4 5 6 7 8 9 |
x |
a matrix or data frame containing the data. |
covariate |
the index of the column in |
grp |
cluster indices for the rows of |
grpcol |
colors corresponding to the clusters. |
grplabel |
cluster names. |
add |
logical indicating whether to start a new plot, or whether to add the plot to the existing one. |
control |
a list of parameters controlling the appearance of the plot, see Details. |
This routine is primarily intended for augmenting heatmaps. It might be useful in other contexts, but misses most frills for using it comfortably.
The following named list elements can be set to change the appearance of the plot:
the relative width of a marking box.
the relative height of a marking box.
the horizontal separation around marking boxes; equals half the horizontal distance between two marking boxes.
ditto for vertical separation.
passed on to loess
used for the smoothing
curve.
color for missing values of binary variables.
if 0, no smoothing line is drawn; otherwise passed on to
loess
used for the smoothing curve.
the character
size for grplabel
.
The plot looks like a more or less derelict picket fence, and 'picketplot' sounds somewhat like the 'pocketplot' used in geostatistics.
Alexander Ploner <Alexander.Ploner@ki.se>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ## Not run:
# without covariate
mm = cbind(sample(0:1, 42, rep=TRUE), sample(0:1, 42, rep=TRUE))
mm[sample(42, 5), 1] = NA
oldPicketplot(mm)
# with clustering
cl = rep(1:3, c(10,22,10))
cn = c("Cluster I","Cluster II","Cluster III")
cc = c("lightblue","lightgreen","lightpink") # windows palette
oldPicketplot(mm, grp=cl, grplabel=cn, grpcol=cc)
# add a covariate; setting the colnames makes the variable labels
mm = cbind(mm, rnorm(42) + cl/2)
colnames(mm) = c("State A","State B", "X")
oldPicketplot(mm, covariate=3,grp=cl, grplabel=cn, grpcol=cc)
# using extra controls
oldPicketplot(mm, covariate=3,grp=cl, grplabel=cn, grpcol=cc, control=list(nacol="white", degree=0))
## End(Not run) ## end dontrun
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