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wired

1.0.1

Weighted Adaptive Prediction with Structured Dependence

0packages depend
1.9Kdownloads / year
63.8%test coverage
13/13checks pass

Overview

About
Maintained by Giancarlo VercellinoFirst published 2026-02-062 releasesCRAN page ↗

Builds a joint probabilistic forecast across series and horizons using adaptive copulas (Gaussian/t) with shrinkage-repaired correlations. At the low level it calls a probabilistic mixer per series and horizon, which backtests several simple predictors, predicts next-window Continuous Ranked Probability Score (CRPS), and converts those scores into softmax weights to form a calibrated mixture (r/q/p/dfun). The mixer blends eight simple predictors: a naive predictor that wraps the last move in a PERT distribution; an arima predictor using auto.arima for one-step forecasts; an Exponentially Weighted Moving Average (EWMA) gaussian predictor with mean/variance under a Gaussian; a historical bootstrap predictor that resamples past horizon-aligned moves; a drift residual bootstrap predictor combining linear trend with bootstrapped residuals; a volatility-scaled naive predictor centering on the last move and scaling by recent volatility; a robust median mad predictor using median/MAD with Laplace or Normal shape; and a shrunk quantile predictor that fits a few quantile regressions over time and interpolates to a full predictive. The function then couples the per-series mixtures on a common transform (additive/multiplicative/log-multiplicative), simulates coherent draws, and returns both transformed- and level-scale samplers and summaries.

Install

Health

CRAN checks
13OK
Slowest check: 7.8 min · r-oldrel-windows-x86_64
Code health
Yes
Tests · ratio 0.09
63.8%
Coverage · measured lines
100%
Documentation · exports
5
Dependencies · direct
Check history
  • OK2026-08-04
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-06-09
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-06-08
    12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • OK2026-03-10
    14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesNopkgdown siteNoNEWSYes · 67% structuredCode of conductNoContributing guideNo
Examples that run
0%
Documented parameters
89%
Return-value docs
100%
References docs
0%

Downloads

1.9K
CRAN downloads in the past year
Rank #11,070 · ~5/day · ~160/mo
Daily download trend is not available in this view yet.
16330 days
88390 days
1.9K1 year
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Dependencies

Declared dependencies
6 external dependencies (excludes base and recommended)
Depends (1)
R >= 4.1.0
LinkingTo (0)
none
Suggests (2)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (1)
Maintainer (1)
Author, Maintainer, Copyright holder
Authors (1)
Author, Maintainer, Copyright holder
Copyright holders (1)
Author, Maintainer, Copyright holder
Package Timeline

2 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.1Latest
    2026-04-13 · current release · diff ↗
  • 1.0.0
    2026-03-10
  • R
    R 4.5.0 released · 2025-04-11

Package metadata

First published
2026-02-06
Total releases
2 / 1 yrs
License
GPL-3 OSI
Minimum R
≥ 4.1.0
Download size
20 KB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("wired")
Vercellino, G. (2026). wired: Weighted Adaptive Prediction with Structured Dependence (Version 1.0.1) [Computer software]. https://doi.org/10.32614/CRAN.package.wired

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for wired version 1.0.1 [Data set]. HJJB, LLC. Data release v2026-08-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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