shingle(x, intervals=sort(unique(x)))
equal.count(x, ...)
as.shingle(x)
is.shingle(x)
## S3 method for class 'shingle':
plot(x, col, aspect, \dots)
## S3 method for class 'shingle':
print(x, showValues = TRUE, \dots)
## S3 method for class 'shingleLevel':
print(x, \dots)
## S3 method for class 'shingle':
summary(object, \dots)
## S3 method for class 'shingle':
as.data.frame(x, row.names = NULL, optional = FALSE)
## S3 method for class 'shingle':
[(x, subset, drop = FALSE)
as.factorOrShingle(x, subset, drop)x$intervals for levels.shingle(x), 
  logical for is.shingle, an object of class ``trellis'' for
  plot (printed by default by print.trellis), and 
  an object of class ``shingle'' for the others.levels and
  nlevels functions, usually applicable to factors, are also
  applicable to shingles.  There are print methods for shingles, as well as for printing the
  result of levels() applied to a shingle.
The implementation of shingles is slightly different from S.
  equal.count converts x to a shingle. Essentially a
  wrapper around co.intervals. All arguments are passed to
  co.intervals
  shingle creates a shingle using the given intervals. If
  intervels is a vector, these are used to form 0 length
  intervals.
  as.shingle returns shingle(x) if x is not a
  shingle.
  is.shingle tests whether x is a shingle.
  plot.shingle displays the ranges of shingles via
  rectangles. print.shingle and summary.shingle describe
  the shingle object.
xyplot,
  co.intervals, Latticez <- equal.count(rnorm(50))
plot(z)
print(z)
print(levels(z))
<testonly>data.frame(x = equal.count(rnorm(100)), y = rnorm(100))</testonly>Run the code above in your browser using DataLab