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mrf

Multiresolution Forecasting

v0.1.9 · Apr 16, 2026 · GPL-3

Description

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>.

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Last 90 days

1.5K

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0

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29

Last 90 days

90

Last year

Trend: -100% (30d vs prior 30d)

autoCRAN

4

Last 7 days

13

Last 30 days

1

All-time

autoCRAN-only: this name is served only by autoCRAN, so the count is exact.

CRAN Check Status

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r-devel-linux-x86_64-fedora-gcc OK
r-devel-windows-x86_64 OK
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Check History

OK 13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Jun 9, 2026
ERROR 12 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE Jun 8, 2026
ERROR r-devel-linux-x86_64-debian-gcc

whether package can be installed

install log ‘’ does not exist
OK 7 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Apr 17, 2026

Code

Structure

Lines of code

3,207

Files

44

Compiled share

0%

Has compiled src

No

Language breakdown

R 1,963 (61.2%)Docs 1,135 (35.4%)Vignettes 109 (3.4%)

API

Exported functions

15

Internal functions

11

Recent export changes

v0.1.5+15 mrf_elm_forecast, mrf_model_selection, mrf_forecast +12 more

Testing & CI

Has tests

No

Test-to-code ratio

0.00

testthat edition

CI present

No

CI type

[]

PR gated

No

Docs

Return-value doc rate

100%

\dontrun example ratio

12.5%

Roxygen coverage

100%

Has pkgdown

No

NEWS present

No

Health & Security signals

Informational signals; not verdicts.

on.exit coverage

Unsafe pattern score

0

Dep constraint coverage

0%

Secret pattern count

0

Bundled 3rd-party code

2 items

Portability & License

Min R version

3.5.0

System requirements

C++ standard

License

GPL-3

License flags

SPDX valid, OSI approved

History

Versions

3

First release

2021-09-22

Latest release

2026-04-16

Avg cadence

834 days

Cold removal rate

Dep drift

3

LOC over versions

v0.1.5: 3,122 LOCv0.1.6: 3,122 LOCv0.1.9: 3,207 LOC

Per-file churn detail lives in the source pipeline: https://github.com/r-observatory/cran-code-metrics.

Dependency Network

Dependencies Reverse dependencies DEoptim forecast monmlp nnfor wavelets mrf

Version History

3 tracked
new 0.1.9 Apr 16, 2026
update 0.1.6 ← 0.1.5 diff Feb 22, 2022
new 0.1.5 Sep 21, 2021