I would like to decompose a time series that does not have cycles. I use the use the decompose() method from stats package like it is used here: https://fukamilab.github.io/BIO202/09-A-time-series.html. In another thread (Decomposition of time series yields error) I was told to prespecify a frequency for the decompositon. But if the time series does not have cycles I am wondering why I should do that. For me it does not make sense and I would like to decompose a time series without prespecifying a frequency.
Does anyone else have an opinion on the approach of predefining a frequency before the decomposition (altough there are no real cycles) and then let a decomposition function extract cycles based on this pre-specified frequency. As mentioned above, I personally think that this is pointless. So basically my question is whether there are methods that do not need a predefined frequency (if the time series has no cycles) to decompose the time series into a trend and a white noise?
I'd appreciate any comments and would be thankful for your help.