I have unevenly sampled data. I tried FFT, and failed. I tried Lomb-Scargle (LS) transformation, and it succeeded.
Here's what I understand about FFT vs LS. Correct me if I'm wrong.
- FFT requires constant sampling rate.
- If data has constant sampling rate, FFT is a better choice than LS
- Periodogram obtained by LS is histogram, and does not preserve amplitude of the original data.
- Y-axis of LS periodogram is called LS Power
I don't know how LS power is computed, but I know that it does not contain information about amplitude. I want to scale my Lomb-scargle periodogram so that it contains information about the amplitude of the original data.
So here's what I'm trying to do:
I take absolute difference of amplitudes over an interval, divide by the length of the intervals, and sum them up.
Is this a valid approach? I feel its not, because the absolute difference in magnitude depends on when you sampled them.
If my approach is wrong, is there any other way to incorporate information about the original amplitude into LS periodogram?