Violation of IID in Peaks over Threshold I'm using the peaks over threshold method to answer a researchquestion. I'm working with time-series data and the observations are not entirely independent. I know that there is some methods you could apply to make the observations approximately independent as "declustering-method", however my data is quite small which, as for my understandning, leaving not to many observations to fit a Generalized pareto distribution.
My question is - how much of a problem are violation of the IID assumption causing in POT-method? It will probably cause some bias to the results but is it a huge problem?


My question is - how much of a problem are violation of the IID assumption causing in POT-method?

It's hard to say, as this depends on the data. If the data is stationary, and the exceedences occur far apart, then probably not much. If all the exceedences occur in the same place then this would be more of a problem
Is it possible to simulate more similar data, for which you know the true distribution? If so then you could use this to quantify the modelling error
You say the time series is not iid, is it alternatively possible to fit a model to the data so the residuals look iid? That way you could perform POT on the residuals
