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
Author: Washington Junger and Antonio Ponce de Leon
Maintainer: Washington Junger <wjunger at ims.uerj.br>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: TimeSeries
CRAN checks: mtsdi results

Documentation:

Reference manual: mtsdi.pdf

Downloads:

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

Reverse dependencies:

Reverse imports: ForecastComb, GeomComb

Linking:

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