Calculates the
XCOV(series1, series2, norm)
series1 |
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A series or array. |
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series2 |
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A series or array. |
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norm |
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Optional. An integer, the normalization method:
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A series.
W1: gsin(1000, .001, 4)
W2: gsin(1000, .001, 4)
W3: xcov(W1, W2)
Performs the
W1: gsin(1000, .001, 4)
W2: gnorm(1000, .001)
W3: xcov(W1, W1, 1)
W4: xcov(W1, W2, 1)
W3 displays the
The
where E is the expected value operator, x[n] and y[n] are a stationary random processes, μx and μy are the mean values and * indicates complex conjugate. In practice, the
where:
XCOV performs
The output length L is:
L = length(series1) + length(series2) - 1
The zeroth lag component is the mid point of the series.
The BIASED normalization divides the result by N, the maximum length of the input series.
The UNBIASED normalization divides the result by
N - abs(N - i - 1) + 1
where i is the index of the result with a start value of 1. For a 0 start index, the unbiased estimate becomes:
The
See FXCOV for the frequency domain implementation.