StempCens: Spatio-Temporal Estimation and Prediction for Censored/Missing Responses

It estimates the parameters of spatio-temporal models with censored or missing data using the SAEM algorithm (Delyon et al., 1999). This algorithm is a stochastic approximation of the widely used EM algorithm and is particularly valuable for models in which the E-step lacks a closed-form expression. It also provides a function to compute the observed information matrix using the method developed by Louis (1982). To assess the performance of the fitted model, case-deletion diagnostics are provided.

Version: 1.2.0
Imports: Rcpp, stats, utils, mvtnorm, tmvtnorm, MCMCglmm, ggplot2, grid, Rdpack
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat
Published: 2025-06-11
DOI: 10.32614/CRAN.package.StempCens
Author: Larissa A. Matos ORCID iD [aut, cre], Katherine L. Valeriano ORCID iD [aut], Victor H. Lachos ORCID iD [ctb]
Maintainer: Larissa A. Matos <larissa.amatos at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: StempCens citation info
Materials: README NEWS
In views: MissingData
CRAN checks: StempCens results

Documentation:

Reference manual: StempCens.pdf

Downloads:

Package source: StempCens_1.2.0.tar.gz
Windows binaries: r-devel: StempCens_1.2.0.zip, r-release: StempCens_1.1.0.zip, r-oldrel: StempCens_1.2.0.zip
macOS binaries: r-release (arm64): StempCens_1.2.0.tgz, r-oldrel (arm64): StempCens_1.2.0.tgz, r-release (x86_64): StempCens_1.1.0.tgz, r-oldrel (x86_64): StempCens_1.1.0.tgz
Old sources: StempCens archive

Reverse dependencies:

Reverse imports: RcppCensSpatial

Linking:

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