Implements a probabilistic ensemble time-series forecaster that combines an auto-encoder with a neural decision forest whose split variables are learned through a differentiable feature-mask layer. Functions are written with 'torch' tensors and provide CRPS (Continuous Ranked Probability Scores) training plus mixture-distribution post-processing.
| Version: | 1.1.0 |
| Depends: | R (≥ 4.1.0) |
| Imports: | torch (≥ 0.11.0), purrr (≥ 1.0.1), imputeTS (≥ 3.3), lubridate (≥ 1.9.2), ggplot2 (≥ 3.5.1), scales (≥ 1.3.0) |
| Suggests: | knitr, testthat (≥ 3.0.0) |
| Published: | 2025-08-18 |
| DOI: | 10.32614/CRAN.package.temper |
| Author: | Giancarlo Vercellino [aut, cre, cph] |
| Maintainer: | Giancarlo Vercellino <giancarlo.vercellino at gmail.com> |
| License: | GPL-3 |
| URL: | https://rpubs.com/giancarlo_vercellino/temper |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | temper results |
| Reference manual: | temper.html , temper.pdf |
| Package source: | temper_1.1.0.tar.gz |
| Windows binaries: | r-devel: temper_1.1.0.zip, r-release: temper_1.1.0.zip, r-oldrel: temper_1.1.0.zip |
| macOS binaries: | r-release (arm64): temper_1.1.0.tgz, r-oldrel (arm64): temper_1.1.0.tgz, r-release (x86_64): temper_1.1.0.tgz, r-oldrel (x86_64): temper_1.1.0.tgz |
| Old sources: | temper archive |
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