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Refers to a general class of methods used to "fill in" missing data. Methods used for doing this typically are related to interpolation (http://en.wikipedia.org/wiki/Interpolation) and require assumptions about why the data is missing (e.g. "missing at random")
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Imputation for Time Series of Accumulated Value
Consecutive accumulated data is functional not stochastic, thus, it does not form the assumption to use time series. It would be better to difference the data first to get the new records at each time …