I have univariate temporal data set, with missing data up to 15% over a year. Are time series analysis models can be used to impute these missing data ?
What I would like to know is: are time series forecasting models (AR, ARMA, ...) can be also used for the imputation of missing data. I suppose that initially, the model was built from the complete data.
You may look at the Missing Data Imputation algorithms provided in the following two papers. These algorithms were implemented in R. I can share with you the codes if you think they are useful to you.
Conference Paper Comparative Statistical Algorithms for Imputation of Missing...
Conference Paper Efficient Imputation of Incomplete Petrophysical Dataset thr...