Sorry for the vagueness of the title, I am having a hard time even coming up with sort of problem I am facing (if there is a specific name for it....)
In a nutshell, I have a time series of points, something of this sort:
Y1,0,0,Y4,0,Y6,0,Y8,0,0,... (this would be the y-axis of the graph, each point represents a time T, and each point is equally spaced out in terms of time.
The Problem: The 0 values denote a time were a cycle has been missed. The Y values denote the Y value at that time, and possibly, also previous value(s) that were missed before, meaning that, Y4 could potentially contain the actual value of Y2 and Y3 (other than its value), something like so:
5,0,0,15,0,5,0,15,0,0. In reality, the actual Y values would be something of the sort:
5,5,5,5,5,5,5,5,0,0. So basically, some of the values are deflated (0), and the others, are inflated (Y). (In a real case scenario the Y values would fluctuate, forming peaks and troughs).
So basically I have two types of values:
- Values which are deflated (represented by a 0).
- Values which are inflated (represented by anything greater than 0).
The issue is that these values always fluctuate. I was thinking of applying something similar to a rolling average, but that approach appeared too naive for my taste.
Is there something I can look into?