Computes discrete auto or cross covariance
[c, lagindex] = xcov(x) [c, lagindex] = xcov(x, y) [c, lagindex] = xcov(.., maxlags) [c, lagindex] = xcov(.., maxlags, scaling)
a vector of real or complex floating point numbers.
a vector of real or complex floating point numbers. The
default value is x
.
a scalar with integer value greater than 1. The default value
is n
. Where n
is the maximum
of the x
and y
vector
length.
a character string with possible value:
"biased"
, "unbiased"
,
"coeff"
, "none"
. The default
value is "none"
.
a vector of real or complex floating point numbers with same
orientation as x
.
a row vector, containing the lags index corresponding to the
c
values.
c=xcov(x)
computes the un-normalized discrete covariance:
c
the sequence of covariance lags Ck=-n:n where
n
is the length of x
xcov(x,y)
computes the un-normalized discrete cross covariance:
c
the sequence of cross covariance lags
Ck=-n:n where n
is the maximum of
x
and y
length's.If the maxlags
argument is given
xcov
returns in c
the sequence of
covariance lags Ck=-maxlags:maxlags. If
maxlags
is greater than length(x)
,
the first and last values of c
are zero.
The scaling
argument describes how
C(k) is normalized before being returned in
c
:
c=
C/n
.c=
C./(n-(-maxlags:maxlags))
.c=
C/(norm(x)*norm(y))
.x
and y
and only return in c
the sequence of covariance lags Ck≥0
.xcorr(x-mean(x),y-mean(y),...)
.t = linspace(0, 100, 2000); y = 0.8 * sin(t) + 0.8 * sin(2 * t); [c, ind] = xcov(y, "biased"); plot(ind, c) | ![]() | ![]() |
Version | Description |
5.4.0 | xcov added. |