I have some data which is recordings of noise levels within a cellular network, noise value vs. time. In the middle of the night the levels return to normal operating levels which are typically -105dBm while during the day these values fluctuate depending upon the number of users and how much data they are pushing/pulling over the air, values can reach -90dBm during busy hour (4-7pm).
In my recordings I have some samples that are missing, they were either never recorded or there was some intervention on the site and there was no data recorded while the site was off air.
If I wish to impute this missing data what considerations do i need to factor in? There is a time series imputation package in R with a variety of methods but I am unsure as to which method is most appropriate. Any pointers would be greatly appreciated.