I have various sets of irregular interval time series data to which I want to apply some sort of smoothing algorithm to produce a good fit.
I have attempted various methods which all were unsatisfactory.
- Loess - Too much of a tendency to overshoot/overreact to outliers
- Moving Average - The lag is unacceptable
I have read about the "Improved Holt Method for Irregular Time Series", but the paper was too difficult for me to understand and implement in C#.
Can someone point me to a good method / algorithm which produces good smoothing?
The method must be able to calculate the smoothed point at time $t$, without requiring $t+1$, etc., data. It also must be capable of dealing with multiple $y$ values for a given $x$ time.