which algorithms can be used to extrapolate non-linear data?

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I have a dataset, where target value changes in time in following way:

enter image description here

I need to predict target value for upcoming month, however I struggle to find a method to extrapolate the function that defines target. It is certainly not linear.

I tried to extrapolate the max/min peaks separately using linear regression, but not sure what to do with all other values.

Eldar

Posted 2020-01-25T14:55:58.787

Reputation: 53

If it were that same kind of pattern but without the increasing amplitude, what would you do? – Dave – 2020-01-25T15:24:40.717

I would calculate the period of this pattern and predict the same values based on position inside the pattern. – Eldar – 2020-01-25T18:35:47.843

I would say to do something similar but calculate some kind of stretching constant. The amplitude seems to be increasing linearly. – Dave – 2020-01-26T01:51:18.813

Thanks, that seems like a reasonable thing to do. Do you have any suggestions about the models that can handle such constant? – Eldar – 2020-01-26T20:14:21.327

I would do something with how the high peaks increase and how the low peaks decrease and use those seemingly linear trends to say how the shape is getting stretched up and down. The stretching up is more pronounced than the stretching down. – Dave – 2020-01-26T21:30:36.993

Answers

1

That function can be decomposed into composite components:

  • General trend
  • Repeated frequencies (looks like there are 3 major cycles)
  • Random noise

A Fourier transform can decompose a function into its constituent frequencies.

Brian Spiering

Posted 2020-01-25T14:55:58.787

Reputation: 10 864