Estimation of scale based on sequential-order differences, corresponding to
the scale estimates provided by var
,
sd
, mad
and
IQR
.
varDiff(x, idxs = NULL, na.rm = FALSE, diff = 1L, trim = 0, ...)sdDiff(x, idxs = NULL, na.rm = FALSE, diff = 1L, trim = 0, ...)
madDiff(x, idxs = NULL, na.rm = FALSE, diff = 1L, trim = 0,
constant = 1.4826, ...)
iqrDiff(x, idxs = NULL, na.rm = FALSE, diff = 1L, trim = 0, ...)
rowVarDiffs(x, rows = NULL, cols = NULL, na.rm = FALSE, diff = 1L,
trim = 0, ..., useNames = TRUE)
colVarDiffs(x, rows = NULL, cols = NULL, na.rm = FALSE, diff = 1L,
trim = 0, ..., useNames = TRUE)
rowSdDiffs(x, rows = NULL, cols = NULL, na.rm = FALSE, diff = 1L,
trim = 0, ..., useNames = TRUE)
colSdDiffs(x, rows = NULL, cols = NULL, na.rm = FALSE, diff = 1L,
trim = 0, ..., useNames = TRUE)
rowMadDiffs(x, rows = NULL, cols = NULL, na.rm = FALSE, diff = 1L,
trim = 0, ..., useNames = TRUE)
colMadDiffs(x, rows = NULL, cols = NULL, na.rm = FALSE, diff = 1L,
trim = 0, ..., useNames = TRUE)
rowIQRDiffs(x, rows = NULL, cols = NULL, na.rm = FALSE, diff = 1L,
trim = 0, ..., useNames = TRUE)
colIQRDiffs(x, rows = NULL, cols = NULL, na.rm = FALSE, diff = 1L,
trim = 0, ..., useNames = TRUE)
Returns a numeric
vector
of
length 1, length N, or length K.
A vector
indicating subset of elements to
operate over. If NULL
, no subsetting is done.
If TRUE
, missing values are
excluded.
The positional distance of elements for which the difference should be calculated.
A double
in [0,1/2] specifying the fraction
of observations to be trimmed from each end of (sorted) x
before
estimation.
Not used.
A scale factor adjusting for asymptotically normal consistency.
A vector
indicating subset of rows to
operate over. If NULL
, no subsetting is done.
A vector
indicating subset of columns to
operate over. If NULL
, no subsetting is done.
If TRUE
(default), names
attributes of the result are set, otherwise not.
Henrik Bengtsson
Note that n-order difference MAD estimates, just like the ordinary MAD
estimate by mad
, apply a correction factor such that
the estimates are consistent with the standard deviation under Gaussian
distributions.
The interquartile range (IQR) estimates does not apply such a
correction factor. If asymptotically normal consistency is wanted, the
correction factor for IQR estimate is 1 / (2 * qnorm(3/4))
, which is
half of that used for MAD estimates, which is 1 / qnorm(3/4)
. This
correction factor needs to be applied manually, i.e. there is no
constant
argument for the IQR functions.
[1] J. von Neumann et al., The mean square successive
difference. Annals of Mathematical Statistics, 1941, 12, 153-162.