The
LNP_TEST
function computes the
Lomb Normalized Periodogram of two sample populations *
X*
and *
Y*
and
tests the
hypothesis that the populations represent a significant periodic signal against the hypothesis that they represent random noise. The result is a two-element vector containing the maximum peak in the Lomb Normalized Periodogram and its significance. The significance is a value in the interval [0.0, 1.0]; a small value indicates that a significant periodic signal is present.

LNP_TEST is based on the routine ```
fasper
```

described in section 13.8 of *
Numerical Recipes in C: The Art of Scientific Computing*
(Second Edition), published by Cambridge University Press, and is used by permission.

Use this keyword to specify the scale factor of the average Nyquist frequency. The default value is 1.

Use this keyword to specify a named variable that will contain the index of the maximum peak in the Lomb Normalized Periodogram.

Define two *
n*
-element sample populations.

X = [ 1.0, 2.0, 5.0, 7.0, 8.0, 9.0, $

10.0, 11.0, 12.0, 13.0, 14.0, 15.0, $

16.0, 17.0, 18.0, 19.0, 20.0, 22.0, $

23.0, 24.0, 25.0, 26.0, 27.0, 28.0]

Y = [ 0.69502, -0.70425, 0.20632, 0.77206, -2.08339, 0.97806, $

1.77324, 2.34086, 0.91354, 2.04189, 0.53560, -2.05348, $

-0.76308, -0.84501, -0.06507, -0.12260, 1.83075, 1.41403, $

-0.26438, -0.48142, -0.50929, 0.01942, -1.29268, 0.29697]

Test the hypothesis that *
X*
and *
Y*
represent a significant periodic signal against the hypothesis that they represent random noise.

result = LNP_TEST(X, Y, WK1 = wk1, WK2 = wk2, JMAX = jmax)

The small value of the significance represents the possibility of a significant periodic signal. A larger number of samples for *
X*
and *
Y*
would produce a more conclusive result. WK1 and WK2 are both 48-element vectors containing linear frequencies and corresponding Lomb values, respectively. JMAX is the indexed location of the maximum Lomb value in WK2.