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.