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Multiresolution Forecasting

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2.5Kdownloads / year
–test coverage
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Overview

About
Maintained by Quirin StierCRAN page ↗GitHub ↗Website ↗Issues ↗Declared funder: Michael Thrun

Forecasting of univariate time series using feature extraction with variable prediction methods is provided. Feature extraction is done with a redundant Haar wavelet transform with filter h = (0.5, 0.5). The advantage of the approach compared to typical Fourier based methods is an dynamic adaptation to varying seasonalities. Currently implemented prediction methods based on the selected wavelets levels and scales are a regression and a multi-layer perceptron. Forecasts can be computed for horizon 1 or higher. Model selection is performed with an evolutionary optimization. Selection criteria are currently the AIC criterion, the Mean Absolute Error or the Mean Root Error. The data is split into three parts for model selection: Training, test, and evaluation dataset. The training data is for computing the weights of a parameter set. The test data is for choosing the best parameter set. The evaluation data is for assessing the forecast performance of the best parameter set on new data unknown to the model. This work is published in Stier, Q.; Gehlert, T.; Thrun, M.C. Multiresolution Forecasting for Industrial Applications. Processes 2021, 9, 1697. doi:10.3390/pr9101697.

Install

Health

CRAN checks
13OK
Slowest check: 2.5 min · r-oldrel-macos-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK13 OK2026-06-09
  • ERROR12 OK, 1 ERROR2026-06-08
  • OK7 OK2026-04-17
Advisories

none known

Documentation

In release 0.1.9
READMENoVignettesYes · 1 · staticNEWSNoCitation fileNoWebsiteYes
Help pages
17includes a package overview page
Examples that run
88%14 run in a plain check · 2 only when donttest examples are enabled (R CMD check --as-cran)
Exported functions with examples
100%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
94%
Vignettes (1)

Downloads

2.5K
CRAN downloads in the past year
Rank #11,718 · ~7/day · ~211/mo
Daily download trend is not available in this view yet.
37530 days
91890 days
2.5K1 year
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Repository

2Stars
0Forks
0Open issues
0Open PRs
0Releases
24Commits
1Commit identities
24 commits · Last activity 2021-09-23 · 0% stars, 30d · The default branch showed an older version (0.1.6) than CRAN on 2026-10-18
Responsiveness
not measured

Stars over time

2021-10-28 · 22026-07-07 · 2
PracticesBeta

1 development-tooling and community-health practice detected across 1 family in the upstream repository

Checks run against github.com/quirinms/mrfr on 2026-10-18.

Lint, format, editor (1)
RStudio project
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
7 external dependencies (excludes base and recommended)

Installing mrf adds 59 packages (31 with compiled code, 44 MB of source tarballs). Heaviest: ggplot2 6.0 MB, smooth 3.4 MB, glmnet 2.7 MB.

Depends (1)
R >= 3.5.0
Imports (7)
LinkingTo (0)
none
Suggests (2)
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Datasets

People & History

People (2)
Author, Maintainer since 0.1.5 (2021), Contributor
Thesis advisor, Copyright holder, Reviewer, Funder, Contributor
Releases (3)

Pick two releases to compare their code metrics.

  • R
    R 4.6.0 released · 2026-04-24
  • unarchivedReturned to CRAN
    2026-04-16
  • 0.1.9Latest
    record
    2026-04-16 · current release · diff ↗
  • archivedRemoved from CRAN
    2025-06-02
    requires archived package 'limSolve'
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • 0.1.6
    record
    2022-02-23 · diff ↗
  • 0.1.5
    record
    2021-09-22
  • R
    R 4.1.0 released · 2021-05-18

Package metadata

First published
2021-09-22
Total releases
3 / 5 yrs
License
GPL-3 OSI
Minimum R
≥ 3.5.0
Bundled data
32 KB / 1 file
Download size
83 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("mrf")
Stier, Q., & Thrun, M. (2026). mrf: Multiresolution Forecasting (Version 0.1.9) [Computer software]. https://doi.org/10.32614/CRAN.package.mrf

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.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for mrf version 0.1.9 [Data set]. HJJB, LLC. Data release v2026-10-20. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-20, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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