| varDiff {matrixStats} | R Documentation |
Estimation of scale based on sequential-order differences
Description
Estimation of scale based on sequential-order differences, corresponding to
the scale estimates provided by var,
sd, mad and
IQR.
Usage
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)
Arguments
x |
|
idxs |
A |
na.rm |
If |
diff |
The positional distance of elements for which the difference should be calculated. |
trim |
A |
... |
Not used. |
constant |
A scale factor adjusting for asymptotically normal consistency. |
rows |
A |
cols |
A |
useNames |
If |
Details
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.
Value
Returns a numeric vector of
length 1, length N, or length K.
Author(s)
Henrik Bengtsson
References
[1] J. von Neumann et al., The mean square successive
difference. Annals of Mathematical Statistics, 1941, 12, 153-162.
See Also
For the corresponding non-differentiated estimates, see
var, sd, mad
and IQR. Internally, diff2() is used
which is a faster version of diff().