imputeTS

R package 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’.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 11 articles )

Showing results 1 to 11 of 11.
Sorted by year (citations)

  1. Roy, Arkaprava; Ghosal, Subhashis: Optimal Bayesian smoothing of functional observations over a large graph (2022)
  2. Fernandes, Sofia; Antunes, Mário; Gomes, Diogo; Aguiar, Rui L.: Misalignment problem in matrix decomposition with missing values (2021)
  3. Kalantari, Mahdi: Forecasting COVID-19 pandemic using optimal singular spectrum analysis (2021)
  4. Klaus Nordhausen, Markus Matilainen, Jari Miettinen, Joni Virta, Sara Taskinen: Dimension Reduction for Time Series in a Blind Source Separation Context Using R (2021) not zbMATH
  5. Michał Narajewski, Jens Kley-Holsteg, Florian Ziel: tsrobprep - an R package for robust preprocessing of time series data (2021) arXiv
  6. Müller, Juliane; Park, Jangho; Sahu, Reetik; Varadharajan, Charuleka; Arora, Bhavna; Faybishenko, Boris; Agarwal, Deborah: Surrogate optimization of deep neural networks for groundwater predictions (2021)
  7. Wongoutong, Chantha: Imputation methods in time series with a trend and a consecutive missing value pattern (2021)
  8. Lebacher, Michael; Thurner, Paul W.; Kauermann, Göran: Exploring dependence structures in the international arms trade network: a network autocorrelation approach (2020)
  9. Parrella, Maria Lucia; Albano, Giuseppina; La Rocca, Michele; Perna, Cira: Reconstructing missing data sequences in multivariate time series: an application to environmental data (2019)
  10. Imbert, Alyssa; Vialaneix, Nathalie: Exploring, handling, imputing and evaluating missing data in statistical analyses: a review of existing approaches (2018)
  11. Neeraj Bokde, Kishore Kulat, Marcus W Beck, Gualberto Asencio-Cortes: R package imputeTestbench to compare imputations methods for univariate time series (2016) arXiv