Ok you have a time series like this:
0, 30, 90, 110, NA, 210, NA, NA, 333,400, NA, 410
So what you probably want to be considered is that:
- The NA replacement is bigger than the value before the NA
- The NA replacement is smaller than the value after the NA
- This still applies for for consecutive missing values
Well, the solution is easy.
Linear Interpolation will fulfill this rules all the time.
(and actually also gives decent results)
But also all other (advanced) time series methods will recognize the clear trend in the data and make use of this.
To get a feeling, what are common time series imputation methods, you could have a look at the manual of my time series imputation R package (imputeTS manual).