mtsdi: Multivariate Time Series Data Imputation

This is an EM algorithm based method for imputation of missing values in multivariate normal time series. The imputation algorithm accounts for both spatial and temporal correlation structures. Temporal patterns can be modeled using an ARIMA(p,d,q), optionally with seasonal components, a non-parametric cubic spline or generalized additive models with exogenous covariates. This algorithm is specially tailored for climate data with missing measurements from several monitors along a given region.

Version: 0.3.5
Depends: R (≥ 3.0.0), utils, stats, gam, splines
Published: 2018-01-23
DOI: 10.32614/CRAN.package.mtsdi
Author: Washington Junger and Antonio Ponce de Leon
Maintainer: Washington Junger <wjunger at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: TimeSeries
CRAN checks: mtsdi results


Reference manual: mtsdi.pdf


Package source: mtsdi_0.3.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mtsdi_0.3.5.tgz, r-oldrel (arm64): mtsdi_0.3.5.tgz, r-release (x86_64): mtsdi_0.3.5.tgz, r-oldrel (x86_64): mtsdi_0.3.5.tgz
Old sources: mtsdi archive

Reverse dependencies:

Reverse imports: ForecastComb, GeomComb


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