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
, Lattice
z <- equal.count(rnorm(50))
plot(z)
print(z)
print(levels(z))
<testonly>data.frame(x = equal.count(rnorm(100)), y = rnorm(100))</testonly>
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