Stronger as in noise-free, which is more important for a real-world signal such as ENSO. There is no noise in this artificial fullwave rectified example, so all that matters is the duration.

Nyquist sampling is important but so is the number of sinusoidal factors that can contribute. Also important is the number of periods that are quite close in value. This takes a longer interval to disambiguate the two.

How it works is just a nonlinear gradient search to find a set of values that maximizes an objective criteria such as the correlation coefficient. From scratch, it takes about 30 minutes to set up in an Excel spreadsheet.

Keep questions coming, if I don't explain lucidly. I am certain to get these equestions again.

There was a paper on how they used it for tidal prediction, which I get back to later.

Nyquist sampling is important but so is the number of sinusoidal factors that can contribute. Also important is the number of periods that are quite close in value. This takes a longer interval to disambiguate the two.

How it works is just a nonlinear gradient search to find a set of values that maximizes an objective criteria such as the correlation coefficient. From scratch, it takes about 30 minutes to set up in an Excel spreadsheet.

Keep questions coming, if I don't explain lucidly. I am certain to get these equestions again.

There was a paper on how they used it for tidal prediction, which I get back to later.