corrfun

Compute the autocorrelation or cross-correlation function.

Usage

corrfun(xvector {, n {, scale {, cyclic}}})	... autocorrelation of x
corrfun(xvector, yvector {, n {, scale {, cylic}}})	... cross correlation of x and y

x, y

data vectors

n

the number of lags; 0 < n < ncol(x) (default=ncol(x)/2)

scale

specifies the scaling of the function:

scale=0	... no scaling (default)
scale=1	... "biased", each lag i is scaled by the length of x (1/ncol(x))
scale=2	... "unbiased", each lag i is scaled by the number of correlated elements (1/(ncol(x)-i))

cyclic

normal or cyclic indexing

cyclic=0	... normal (default); (acf[i]=sum(x[t]*y[t+i], t=0..ncol(x)-1-i))
cyclic!=0	... cyclic; (acf[i]=sum(x[t]*y[(t+i)%ncol(x)], t=0..ncol(x)-1))

Result

The autocorrelation function of the data vector x or the cross correlation function of the vectors x and y. The result is a scalar (if n=1) or a vector with n elements.

See also

corr

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