Is there any time series model which handles data at variable frequencies.?

Question

Goal: Predict the yellow points.(yellow events appear at varying frequencies)

But I'm struggling to find a good model to fit this use case. 
Most of the time series algorithms are handling data which are at same frequencies(like per day/every 10 secs). I tried a lot of stuff but may be completely on the wrong approach.

Thanks a lot for any hint!!!

saravanan saminathan · Answer

It looks like stock price data. You can use fbprophet(python),BATS(R),TBATS(R) to predict the data. 
You said your model contains different frequencies which mean it contains more than one seasonality.
To find seasonality(frequencies) you can use Fourier transform. You should have significant data to get a good prediction

Adeetya · Answer

Little more insight than just a graph is needed.
Like what all features along with the type of data. 
If it's just this graph then

Data might be coming from a scientific instrument as per y-axis reading.
Try identifying the trend and seasonality and noise by first decomposing it.
You can go for LSTM as they are pretty good at handling time series.

Is there any time series model which handles data at variable frequencies.?

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