x: Input, numeric or complex vector or matrix. Must not be missing.
y: Input, numeric or complex vector data. If x is a matrix (not a vector), y must be omitted. y may be omitted if x is a vector; in this case xcov estimates the autocovariance of x.
maxlag: Integer scalar. Maximum covariance lag. If omitted, the default value is N-1, where N is the greater of the lengths of x and y or, if x is a matrix, the number of rows in x.
scale: Character string. Specifies the type of scaling applied to the covariation vector (or matrix). matched to one of:
"none": return the unscaled covariance, C
"biased": return the biased average, C/N
"unbiased": return the unbiased average, C(k)/(N-|k|)
"coeff": return C/(covariance at lag 0)
If omitted, the default value is "none". If y is supplied but does not have the same length as x, scale must be "none".
Returns
A list containing the following variables:
C: array of covariance estimates
lags: vector of covariance lags [-maxlag:maxlag]
The array of covariance estimates has one of the following forms:
Cross-covariance estimate if X and Y are vectors.
Autocovariance estimate if is a vector and Y is omitted.
If x is a matrix, C is a matrix containing the cross-covariance estimates of each column with every other column. Lag varies with the first index so that C has 2 * maxlag + 1 rows and P2 columns where P is the number of columns in x.