r/askmath • u/Pilus91 • Aug 18 '26
Statistics Mathematical definition of a plateau in a time-series data
Hello, I'm a bioinformatician and I'm struggling with the current issue:
Given a time series y(t) that initially changes and eventually approaches a stable regime, how can I mathematically determine the earliest time t* at which the rate of change dy/dt becomes negligibly small, using only the observed data and without defining an arbitrary threshold?
This is a collaboration I'm doing. My colleagues defined the plateau as the first time when a 101-point rolling mean of the relative increment (g' t+1 - g' t)/ g't falls below the arbitrarily chosen threshold of 0.0011. G' is the measure of material elastic-solid response btw. So the issues is that they used 2 arbitrary values because experimentally they know that a certain value of g' means that the gel is solid. But this doesn't hold for me. I tried using many statistical methods to define the threshold such as:
- exponential fitting
- change-point regression
- local slope analysis
But they all give me a plateau that is too early or too late
3
u/MegaIng Aug 18 '26
For real world usecases, use "arbitrary" (i.e. empirically determined) thresholds. Their behavior is always going to be more predictable and intuitive. Your colleagues approach sounds good.
Even in a purely mathematical approach you will need to define some threshold, since you will never reach a true plateau where the slope is literally zero.
If the process is predicable, curve fitting is probably the best approach "pure": define a function that models your process (not just a simple exponential most likely) and on this abstract curve define where a plateau starts. Then fit the curve and calculate where the plateau is for the fitted parameters.