varDiff | R Documentation |
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)
x |
A |
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 |
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.
Returns a numeric
vector
of
length 1, length N, or length K.
Henrik Bengtsson
[1] J. von Neumann et al., The mean square successive
difference. Annals of Mathematical Statistics, 1941, 12, 153-162.
For the corresponding non-differentiated estimates, see
var
, sd
, mad
and IQR
. Internally, diff2
() is used
which is a faster version of diff
().
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