xpect: Probabilistic Time Series Forecasting with XGBoost and Conformal
Inference
Implements a probabilistic approach to time series forecasting combining XGBoost regression with conformal inference methods. The package provides functionality for generating predictive distributions, evaluating uncertainty, and optimizing hyperparameters using Bayesian, coarse-to-fine, or random search strategies.
Version: |
1.0 |
Depends: |
R (≥ 2.10) |
Imports: |
normalp (≥ 0.7.2), glogis (≥ 1.0-2), gld (≥ 2.6.6), edfun (≥ 0.2.0), purrr (≥ 1.0.1), ald (≥ 1.3.1), evd (≥ 2.3-6.1), GeneralizedHyperbolic (≥ 0.8-6), cubature (≥ 2.1.0), furrr (≥ 0.3.1), future (≥ 1.33.0), xgboost (≥ 1.7.5.1), rBayesianOptimization (≥ 1.2.0), lubridate (≥ 1.9.2), ggplot2 (≥ 3.5.1), scales (≥ 1.3.0) |
Suggests: |
testthat (≥ 3.0.0) |
Published: |
2025-03-24 |
DOI: |
10.32614/CRAN.package.xpect |
Author: |
Giancarlo Vercellino [aut, cre, cph] |
Maintainer: |
Giancarlo Vercellino <giancarlo.vercellino at gmail.com> |
License: |
GPL-3 |
URL: |
https://rpubs.com/giancarlo_vercellino/xpect |
NeedsCompilation: |
no |
Materials: |
NEWS |
CRAN checks: |
xpect results |
Documentation:
Downloads:
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