Temporal Encoder-Masked Probabilistic Ensemble Regressor
Overview
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.
- Improved CRAN compatibility by making torch-based examples and tests run only when the full torch runtime is available.
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-04
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-03-10
Documentation
- Help pages
- 2includes a package overview page
- Examples that run
- 100%2 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- unarchivedReturned to CRAN2026-07-16
- 1.1.1Latest
- archivedRemoved from CRAN2026-04-28issues were not corrected in time
- RR 4.6.0 released · 2026-04-24
- 1.1.02025-08-18 · diff ↗
- 1.0.02025-07-15
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2025-07-15
- Total releases
- 3 / 1 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 4.1.0
- Bundled data
- 21 KB / 1 file
- Download size
- 35 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("temper")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.