imputeTS: Time Series Missing Value Imputation

Imputation (replacement) of missing values in univariate time series. Offers several imputation functions and missing data plots. Available imputation algorithms include: 'Mean', 'LOCF', 'Interpolation', 'Moving Average', 'Seasonal Decomposition', 'Kalman Smoothing on Structural Time Series models', 'Kalman Smoothing on ARIMA models'.

Version: 2.7
Depends: R (≥ 3.0.1)
Imports: stats, stinepack, graphics, grDevices, forecast, magrittr, Rcpp
LinkingTo: Rcpp
Suggests: testthat, utils, zoo, timeSeries, tis, xts
Published: 2018-06-20
Author: Steffen Moritz ORCID iD [aut, cre, cph]
Maintainer: Steffen Moritz <steffen.moritz10 at>
License: GPL-3
NeedsCompilation: yes
Citation: imputeTS citation info
Materials: README NEWS
In views: TimeSeries
CRAN checks: imputeTS results


Reference manual: imputeTS.pdf
Vignettes: imputeTS: Time Series Missing Value Imputation in R
Package source: imputeTS_2.7.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: imputeTS_2.7.tgz, r-oldrel: imputeTS_2.7.tgz
Old sources: imputeTS archive

Reverse dependencies:

Reverse imports: hpiR, imputeTestbench
Reverse suggests: baytrends, naniar


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