
; Define two n-element sample populations:
x = [3.73, 3.67, 3.77, 3.83, 4.67, 5.87, 6.70, 6.97, 6.40, 5.57]
y = [2.31, 2.76, 3.02, 3.13, 3.72, 3.88, 3.97, 4.39, 4.34, 3.95]

lag = [-3, 0, 1, 3, 4, 8] 
result = a_correlate(x, lag)
print, "Autocorrelation", result
print, "Expected:   0.0146186      1.00000     0.810879    0.0146186 " + $
       "-0.325279    -0.151684" 
result = a_correlate(x, lag, /covariance)
print, "Autocovariance ", result
print, "Expected:     0.0234569      1.60460      1.30113    0.0234569 " + $
       "-0.521942    -0.243391"
print

lag = [-5, 0, 1, 5, 6, 7] 
result = c_correlate(x, y, lag)
print, "Cross Correlation", result
print, "Expected:    -0.428246     0.914755     0.674547    -0.405139 " + $
       "-0.403099    -0.339684"
result = c_correlate(x, y, lag, /covariance)
print, "Cross Covariance ", result
print, "Expected     -0.360766     0.770614     0.568256    -0.341300 " + $
       "-0.339581    -0.286159"


end

