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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 
[aut, cre],
Katherine L. Valeriano
[aut],
Victor H. Lachos
[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:
Downloads:
Reverse dependencies:
Linking:
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https://CRAN.R-project.org/package=StempCens
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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